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<Paper uid="J87-3009">
  <Title>THE SELF-EXTENDING PHRASAL LEXICON*</Title>
  <Section position="1" start_page="0" end_page="0" type="metho">
    <SectionTitle>
THE SELF-EXTENDING PHRASAL LEXICON*
</SectionTitle>
    <Paragraph position="0"> Lexical representation so far has not been extensively investigated in regard to language acquisition.</Paragraph>
    <Paragraph position="1"> Existing computational linguistic systems assume that text analysis and generation take place in conditions of complete lexical knowledge. That is, no unknown elements are encountered in processing text. It turns out however, that productive as well as non-productive word combinations require adequate consideration. Thus, assuming the existence of a complete lexicon at the outset is unrealistic, especially when considering such word combinations.</Paragraph>
    <Paragraph position="2"> Three new problems regarding the structure and the contents of the phrasal lexicon arise when considering the need for dynamic acquisition. First, when an unknown element is encountered in text, information must be extracted in spite of the existence of an unknown. Thus, generalized lexical patterns must be employed in forming an initial hypothesis, in absence of more specific patterns. Second, senses of single words and particles must be utilized in forming new phrases. Thus the lexicon must contain information about single words, which can then supply clues for phrasal pattern analysis and application. Third, semantic clues must be used in forming new syntactic patterns. Thus, lexical entries must appropriately integrate syntax and semantics.</Paragraph>
    <Paragraph position="3"> We have employed a Dynamic Hierarchical Phrasal Lexicon (DHPL) which has three features: (a) lexical entries are given as entire phrases and not as single words, (b) lexical entries are organized as a hierarchy by generality, and (c) there is not separate body of grammar rules: grammar is encoded within the lexical hierarchy. A language acquisition model, embodied by the program RINA, uses DHPL in acquiring new lexical entries from examples in context through a process of hypothesis formation and error correction. In this paper we show how the proposed lexicon supports language acquisition.</Paragraph>
  </Section>
  <Section position="2" start_page="0" end_page="0" type="metho">
    <SectionTitle>
1. INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> Examination of the language acquisition task sheds light on the nature of the lexicon, illuminating issues which have been ignored by existing linguistic systems \[Wilks75, Kay79, Bresnan82b, Gazdar85\]. Current systems restrict their account to analysis and generation of text, by making the assumption that a fixed, complete lexicon exists at the outset. This assumption proves unrealistic for two reasons: First, due to the huge size of the lexicon (especially when including idioms and phrases) it is difficult to manually encode the entire lexicon. This problem is further aggravated as people *This research was supported in part by a grant from the Initial Teaching Alphabet (ITA) Foundation.</Paragraph>
    <Paragraph position="1"> **Uri Zernik's new address is: General Electric, Research and Development Center, P.O. Box 8 Schenectady NY 12301.</Paragraph>
    <Paragraph position="2"> continuously invent new idiosyncratic word combinations, which are then introduced into general speech. Second, word meanings must often be custom tailored to the domain (e.g., bug in computer applications), since people assign different meanings to words in various jargons. Therefore, computational linguistic models are required to learn lexical items in context, the way people learn new words and phrases.</Paragraph>
    <Paragraph position="3"> Learning commonly occurs when the learner detects a gap in his or her knowledge. In analysis, such a discrepancy can be detected when a new word or phrase is encountered. Learning involves three issues: (a) detecting the discrepancy in the first place, (b) forming an initial hypothesis about the new phrase, and (c) refining and generalizing this hypothesis through a process of error correction \[Granger77, Langley82, Selfridge82, Zernik85b\]. These three issues impose new requirements on the lexicon, regarding (a) its Copyright 1987 by the Association for Computational Linguistics. Permission to copy without fee all or part of this material is granted provided that the copies are not made for direct commercial advantage and the CL reference and this copyright notice are included on the first page. To copy otherwise, or to republish, requires a fee and/or specific permission.  308 Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon contents-the way individual entries are encoded, and (b) its structure-the way entries are organized.</Paragraph>
    <Paragraph position="4">  The need to detect discrepancies affects the contents of the lexicon. Both semantic and syntactic discrepancies must be detected, and correction strategies must be associated with various types of errors. Thus, lexical entries should not be underspecified, lest they will allow discrepancies to slip by unnoticed.</Paragraph>
    <Paragraph position="5"> The need to generalize affects the structure of the lexicon. In order to make an initial hypothesis about a new element, it is important to glean from the text as much information as possible. This requirement is problematic: the text cannot be analyzed since an element is unknown; but on the other hand, for the element to be acquired, the text must be analyzed. The solution for this bootstrapping problem is to employ a lexical hierarchy by generality. When a specific pattern does not exist for a precise matching against the new element, one can apply a more general pattern, which albeit being less informative, does match the new element.</Paragraph>
    <Paragraph position="6"> Thus, we propose employing a Dynamic Hierarchical Phrasal Lexicon (DHPL) which has three features: (a) lexical entries are given as entire phrases and not as single words, (b) phrases are organized in a hierarchy by generality, and (c) there is not separate grammar; grammar is encoded in general lexical phrases. The program RINA \[Zernik86b, Zernik87a\] employs DHPL in modeling language acquisition. In particular, the program models second language acquisition of English phrases and idioms. The linguistic concepts being acquired are complex enough, so that neither a human learner, nor a computer program can acquire their complete behavior through a single example. Thus the initial hypothesis might be incorrect. Capturing incorrect hypotheses generated by humans, and simulating them by the computer program is essential for practical and theoretical reasons. First, the human user of the program will relate to the human-like errors generated by the program. Consequently he may present the program with constructive counterexamples. Second, human errors, such as errors of overgeneralization, reveal otherwise inaccessible cognitive processes and internal structures. Thus, errors made by human learners play a central role in constructing a cognitive model of acquisition. Subsequently, observed human behavior is analyzed in terms of the computer program RINA.</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
1.1 THE LINGUISTIC BEHAVIOR
</SectionTitle>
      <Paragraph position="0"> RINA receives examples from a user who teaches her new phrases. When RINA encounters a new phrase, she creates a hypothesis about its behavior, and accordingly she generates an example to demonstrate her state of knowledge. Communication between the program and the user is only through a sequence of examples there is no way to discuss syntax and semantics explicitly. null</Paragraph>
    </Section>
  </Section>
  <Section position="3" start_page="0" end_page="0" type="metho">
    <SectionTitle>
(1) LEARNING NEW PHRASES
</SectionTitle>
    <Paragraph position="0"> In the following dialog, RINA encounters an unknown phrase, throw the book at somebody.</Paragraph>
    <Paragraph position="1"> User: AI Capone went on trial.</Paragraph>
    <Paragraph position="2"> The judge threw the book at him.</Paragraph>
    <Paragraph position="3"> RINA: He threw a book at him? User: No. The judge threw the book at him. RINA: He punished him severely? RINA is familiar with the single words throw and book. However, the entire figurative phrase is not in her lexicon. RINA first attempts a literal interpretation using a phrase existing in the lexicon (throw an object). When this interpretation fails she realizes the existence of an unknown, and tries to form the meaning of the new phrase by using (a) the context, and (b) the single words in the phrase.</Paragraph>
  </Section>
  <Section position="4" start_page="0" end_page="0" type="metho">
    <SectionTitle>
(2) PROCESSING AN UNKNOWN
</SectionTitle>
    <Paragraph position="0"> In the next dialog, RINA encounters a new word, goggled.</Paragraph>
    <Paragraph position="1"> User: RINA: Jenny goggled John to come over. Jenny told John that he must/can/will come to her.</Paragraph>
    <Paragraph position="2"> RINA manages to extract useful information from the sentence in spite of the missing element. In particular, RINA's hypothesis includes three points:  (a) Jenny's unknown act is a kind ofmtrans* (an act of communication).</Paragraph>
    <Paragraph position="3"> (b) The actor of the communicated event (coming over) is John.</Paragraph>
    <Paragraph position="4"> (c) The communicated event is a conditional plan for  the future (in contrast, for example, to the case: Jenny goggled John that he came over). Normally, properties of an embedded phrase (e.g., to come over) are determined by the definition of the embedding verb. RINA manages to make an initial hypothesis even though the embedding verb (goggle) is unknown, by using generalized knowledge of phrase interaction. (The structure of a sentence: Personl goggled Person2 to do Act3 implies mtrans such as ask, tell and instruct, in contrast to Personl goggled to do Act2 which implies an mbuild, such as decide). The hypothesis must be abstract, since RINA cannot determine at this point whether this mtrans act comes in the sense of allow (can come over), or instruct (must come over). Yet, even this hypothesis may turn out to be incorrect. For example, goggle could mean seduce, or influence in some other way. In either, it is important to come up with a hypothesis which provides a basis for further modification.</Paragraph>
    <Paragraph position="5"> *Conceptual classes such as mtrans, mbuild, select-plan, are based on semantic representation. Several of these elements are taken from Schank's \[Schank77\] system of primitive acts, goals and plans. Mtrans for example represents the transfer of mental information, and mbuild represents the construction of new information in memory. The particular scheme chosen is not so important as the fact that syntactic classes (such as verbs) are organized phrasally in terms of conceptual categories.</Paragraph>
    <Paragraph position="6"> Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 309 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon</Paragraph>
  </Section>
  <Section position="5" start_page="0" end_page="0" type="metho">
    <SectionTitle>
(3) RESOLVING AN AMBIGUITY
</SectionTitle>
    <Paragraph position="0"> AS with human listeners, computer parsers must also be able to interpret text successfully only when supplied the appropriate context \[Zernik86a\]. Consider the following sentence: User: She took it up with her dad.</Paragraph>
    <Paragraph position="1"> RINA: ? Imagine a person hearing a fragment of a conversation between two unknown people, or alternatively, a computer program being given this sentence in isolation. Clearly, in the absence of a context, this sentence does not make complete sense. The pronouns, she and it cannot be resolved in absence of referents which have been introduced in the discourse. In addition, the same phrase will mean different things in different contexts. Consider these two examples.</Paragraph>
    <Paragraph position="2"> plan (John decided to go home). This behavior does not capture verbs such as suggest, require or ten (John told to go sounds incorrect). The speaker faced a generation task in presence of incomplete lexical knowledge about suggest and require, and he resorted to using generalized knowledge. Using such knowledge, an idea could be communicated, albeit grammatically incorrectly.</Paragraph>
    <Paragraph position="3"> Therefore, the lexicon must maintain phrases at various level of generality, to cope with different degrees of partial knowledge.</Paragraph>
    <Paragraph position="4"> (2) USING LINGUISTIC CLUES Meaning representation is extracted from the context. For example, given the text below, AI Capone went on trial.</Paragraph>
    <Paragraph position="5"> The judge threw the book at him.</Paragraph>
    <Paragraph position="6"> User: Jenny wanted to buy a new car.</Paragraph>
    <Paragraph position="7"> She took it up with her dad.</Paragraph>
    <Paragraph position="8"> RINA: She discussed the issue with her dad.</Paragraph>
    <Paragraph position="9"> User: Jenny started jogging.</Paragraph>
    <Paragraph position="10"> She took it up with her dad.</Paragraph>
    <Paragraph position="11"> RINA: She started an activity with him.</Paragraph>
    <Paragraph position="12"> Since the same sentence can be interpreted in two ways in two different contexts, a question is raised regarding disambiguation. What is the impact of the context on phrase selection?</Paragraph>
  </Section>
  <Section position="6" start_page="0" end_page="0" type="metho">
    <SectionTitle>
1.2 ISSUES IN LANGUAGE ACQUISITION
</SectionTitle>
    <Paragraph position="0"> Three lexical representation issues must be addressed in modeling language acquisition.</Paragraph>
  </Section>
  <Section position="7" start_page="0" end_page="0" type="metho">
    <SectionTitle>
(1) USING GENERALIZATIONS
</SectionTitle>
    <Paragraph position="0"> As shown in the sentence below, Jenny goggled John to come over.</Paragraph>
    <Paragraph position="1"> the system must cope with unknown elements. Parts of the text must be examined to some extent, in spite of the presence of the unknown. Ideally, each element in the text is matched by a lexical phrase. Since no such phrase exists for a precise matching of the unknown element, a generalized phrase must be used to recover at least partial information. However, by the nature of generalization, the more generalized the matching phrase, the less informative it is.</Paragraph>
    <Paragraph position="2"> Typical errors of overgeneralization were generated in a version of this paper by the first author, who is a second language speaker: * The third phrase requires to generalize the initial notion. (Section 6) * Wilensky suggested to represent knowledge as a database of rules. (Section 3.2) In both cases, the learner applied the wrong generalized phrase, which accounts for verbs such as decide and RINA guessed that throw the book at somebody means to punish that person severely. However, the context might consist of many concepts, some appropriate and some inappropriate (e.g.: did the judge acquit AI or did he punish him?). Thus, a basic task is feature extraction. In extracting features, the system must utilize clues provided by single words. For example, what is the significance of the particle at? How does it contribute to the construction of the meaning? An experiment with second language speakers reveals, predictably, that using a different preposition leads to a different learning result. When the given text is: AI Capone went on trial.</Paragraph>
    <Paragraph position="3"> The judge threw the book to him.</Paragraph>
    <Paragraph position="4"> language learners formed the hypothesis that the judge actually acquited the defendant. Thus, the lexicon must maintain senses for single words such as at and to that could be used as linguistic clues in feature extraction.</Paragraph>
  </Section>
  <Section position="8" start_page="0" end_page="0" type="metho">
    <SectionTitle>
(3) USING SEMANTIC CLUES
</SectionTitle>
    <Paragraph position="0"> The system must hypothesize the scope and variability of the new phrases. Which one of the phrases below best captures the syntax of the new phrase: the judge threw the book at him? He threw something at him.</Paragraph>
    <Paragraph position="1"> He threw a book at him.</Paragraph>
    <Paragraph position="2"> He threw the book at him.</Paragraph>
    <Paragraph position="3"> Each one of these patterns could be the specification of the new phrase. In determining degree of specificity the system must consult semantic clues extracted during parsing. For example, since no actual book exists in the context, then the reference the book is assumed to be a fixed literal. In contrast, consider the context below: The judge was holding the third volume of tax law. He threw the book at AI.</Paragraph>
    <Paragraph position="4"> 310 Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon In this context, an instance of a book is found in the context (i.e., the third volume), and a different hypothesis is made about the the generality of the new pattern. Thus, semantic discrepancies in parsing must be utilized in determining both scope and generality of syntactic patterns.</Paragraph>
  </Section>
  <Section position="9" start_page="0" end_page="0" type="metho">
    <SectionTitle>
2. ACCOUNTING FOR IDIOMACITY IN THE LEXICON
</SectionTitle>
    <Paragraph position="0"> What are the contents of the lexicon to be acquired? Traditionally, the lexicon has been viewed as a list of words, specifying syntactic and semantic properties for each entry. However, since in our theory, the lexicon provides the sole linguistic database, it must include a variety of linguistic knowledge types, not just properties of single words. Here the lexicon is extended in two ways: towards the specific by bringing in idioms, and towards the general by including grammar.</Paragraph>
  </Section>
  <Section position="10" start_page="0" end_page="0" type="metho">
    <SectionTitle>
2.1 IDIOMS AS EQUAL CITIZENS
</SectionTitle>
    <Paragraph position="0"> Are idioms, such as throw the book at, a class apart, to be distinguished from &amp;quot;normal&amp;quot; phrases, which abide by grammar rules? The first to proclaim &amp;quot;equal rights&amp;quot; for idioms was Becker \[Becker75\], who called for a systematic treatment for the variety of phrases in the language. Consider these phrases: We will be looking forward to seeing you guys.</Paragraph>
    <Paragraph position="1"> He is cheap. He will not pay $5 let alone $8.</Paragraph>
    <Paragraph position="2"> So much for superficial solutions.</Paragraph>
    <Paragraph position="3"> Productive as well as non-productive phrases should reside in the lexicon.</Paragraph>
    <Paragraph position="4"> These phrases defy traditional text-book grammar analysis, however, they possess their own grammar. For example, it sounds odd to say lie is cheap; He will not pay $8 let alone $5 \[Fillmore87\]. (Is the behavior of as well as analogous to the behavior of let alone?) Such linguistic phenomena cannot be ignored merely by tagging it as idiomatic, since idioms turn out to be ubiquitous in people's speech. Hardly can a sentence be found which behaves according to textbook grammar.</Paragraph>
    <Paragraph position="5"> There is a need therefore for a systematic treatment of idiosyncracy \[Fillmore87\]. Furthermore, linguistic knowledge cannot be strictly divided into grammar rules and lexical items. Rather, there is an entire range of items: some very specific, in the sense that they pertain to a small number of instances, and some very general, pertaining to a large number of instances. The former have been called &amp;quot;lexical items&amp;quot;, and the latter &amp;quot;grammar rules&amp;quot;. However, it is not possible to define a clear borderline between such two distinct groups, as elements could be found at all levels of generality, not just at the two ends of the spectrum. On one end, the phrase it is raining cats and dogs is very idiomatic.</Paragraph>
    <Paragraph position="6"> On other end, the phrase in John took the spoon from Uary is an instance of a general verb, to take, which may appear in many other ways. However, consider the phrase John took the issue up with his dad. Is this an idiom, or is it just an instance of the general verb to take?</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
2.2 PRODUCTIVE VS. NON-PRODUCTIVE PHRASES
</SectionTitle>
      <Paragraph position="0"> In the phrasal approach \[Wilensky84\] rather than maintaining lexical entries for single words, the lexicon maintains entire phrases. For example, the lexicon will contain many phrases involving the word throw. Consider these phrases as they appear in the following sentences.</Paragraph>
      <Paragraph position="1">  (I) He threw her off by a single inaccurate clue. (2) He threw a wild party for her graduation.</Paragraph>
      <Paragraph position="2"> (3) He threw up his whole breakfast.</Paragraph>
      <Paragraph position="3"> (4) He threw his weight around.</Paragraph>
      <Paragraph position="4"> (5) He threw a temper tantrum.</Paragraph>
      <Paragraph position="5"> (6) He threw a stone at the kitchen window.</Paragraph>
      <Paragraph position="6"> (7) He threw out that old chapter of his dissertation. (8) He threw out the garbage.</Paragraph>
      <Paragraph position="7"> (9) He threw the banana peel away.</Paragraph>
      <Paragraph position="8"> (10) He threw in the towel.</Paragraph>
      <Paragraph position="9"> (11) He threw the book at his students.</Paragraph>
      <Paragraph position="10"> (12) He threw it. His answer was totally incorrect.  To a certain extent, all the phrases above derive their meanings from the meaning of the verb to throw. However, the issue here is whether a single generic lexical entry for throw can suffice to produce the meanings of all those sentences. In example (6) (he threw a stone), the phrase for throw is used in its generic form and meaning: to throw a physical object means to propel that object through the air. Sentence (9) (he threw away a banana peel) too can be interpreted using the generic phrase. In sentence (8) (he threw out the garbage), on the other hand, the derivation of the meaning using the generic phrase is less direct, as it requires analysis at the level of plans and goals. Throwing an object causes the object to become inaccessible. Thus throwing out the garbage does not necessarily mean throwing it in the air as much as getting rid of it.</Paragraph>
      <Paragraph position="11"> The meanings of the other sentences are even more detached from the generic meaning. The meaning of throw the book (11) at is not a mere composition of the meanings of the single words, but requires extraneous knowledge from the trial situations. Neither a person, nor a computer program can produce the meaning of the phrase if the context is not given. Sentence (4) (he threw his weight around) introduces a metaphor \[LakoffS0\] in which a person's authority is compared to a weight, being used in a careless way. Sentence (2) (he threw a party) as well as sentence (5) (he threw a temper tantrum), use a different meaning of throw (to throw an event) which can hardly be related to its original meaning. Finally, sentence (12) (he threw it) represents a novel, yet still understandable, use of the word throw (as in he blew it).</Paragraph>
      <Paragraph position="12"> Non-productive phrases are those in which the meaning of the entire phrase cannot be produced from the meanings of its constituents. Such phrases should be maintained in the lexicon as distinct entries. In fact, Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 311 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon even productive phrases, such as to throw out the garbage, should be maintained as distinct entries. Even if the meaning can be produced each time from the single words, an objective of an efficient system is to compile knowledge whenever possible, and to minimize unnecessary derivations. Thus, phrases in the lexicon can be viewed as linguistic episodes indexed and compiled for further use. Such knowledge is redundant in regard to language parsing (the meaning could be derived from the constituents again and again). However, this is not the case in language generation, where unless the phrase is stored, it is unlikely to be generated again by the system. Thus, both productive and non-productive phrases must be stored in the lexicon.</Paragraph>
    </Section>
    <Section position="2" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
2.3 FIXED VS. VARIABLE PHRASES
</SectionTitle>
      <Paragraph position="0"> As another example of lexical phrases, consider phrases involving the word at:  (13) John left school at noon. (14) He actually stayed at school for an hour. (15) He dabbled at the piano for a while. (16) John aimed the ball at Mary.</Paragraph>
      <Paragraph position="1"> (17) The criminal is still at large. (18) Mary did not feel at ease in John's presence. (19) This is what I am trying to get at. (20) Did you understand anything at all? (21) Please come at once! (22) John looked at Mary.</Paragraph>
      <Paragraph position="2"> (23) Fred lives at New-York. (produced by a second language speaker.)  Certain phrases are fixed, in the sense that they do not take any variation. For example, at large, at all, or at once are such fixed phrases. One cannot say, for example, at twice. However, other phrases might be mutated and still maintain their basic meaning. For example, at noon, at midnight, at the hour, etc., convey a meaning of sharp timing. Another meaning shared among a set of phrases is described by the following sentences:  (15) He dabbled at the piano for a while. (24) He nibbled at the corn.</Paragraph>
      <Paragraph position="3"> (25) He is playing at AI programming.</Paragraph>
      <Paragraph position="4">  The use of the proposition at here implies an aimless, unfocused activity marking the difference between playing the piano and playing at the piano. Similarly, the set  of sentences: (22) John looked at Mary.</Paragraph>
      <Paragraph position="5"> (26) Spot sniffed at Mary.</Paragraph>
      <Paragraph position="6"> (27) Mary glanced at John.</Paragraph>
      <Paragraph position="7">  share the implication that the sensory act was directed at the object.</Paragraph>
      <Paragraph position="8"> Which ones of these phrases should be maintained in the lexicon? Fixed, idiosyncratic phrases such as at large, at once, and at all must be maintained in the lexicon. Otherwise they cannot be predicted by the system. However, the dilemma arises regarding variable phrases, such as in (22), (26) and (27). The question is whether to maintain all instances of a certain variable phrase or to maintain a single generalized entry which encompasses them all. We argue that both must be maintained. Specific phrases must be maintained as compiled, easy to access knowledge, while general phrases, which can derive many specific phrases, must be maintained too so that the system has a predictive power. Using such generalized phrases, the system can handle instances which have not been previously encountered. null In fact, specific &amp;quot;canned&amp;quot; phrases could not account for the following generation task, concerning the selection of appropriate prepositions in the following sentences: (28) There is one teacher {in on at} our school, which I really like.</Paragraph>
      <Paragraph position="9"> (29) I stayed late {in on at} school.</Paragraph>
      <Paragraph position="10"> Notice that since both sentences involve the word school, it could not be used as a discriminator. Unless the lexicon maintains general predicates for the use of in, at, and on, the generator cannot select the appropriate preposition in each case. Clearly, it is difficult to capture the intuition of a native speaker in forming the general senses of these prepositions. An approximation of this intuition can be captured by modeling a second-language speaker who might &amp;quot;incorrectly&amp;quot; generate a sentence such as (23) above: (23) Fred lives at New York.</Paragraph>
      <Paragraph position="11"> Although it does not sound right to an English speaker, this sentence reflects the notion of that particular speaker.</Paragraph>
    </Section>
  </Section>
  <Section position="11" start_page="0" end_page="0" type="metho">
    <SectionTitle>
2.40VERSPECIFICATION AND UNDERSPECIFICATION
</SectionTitle>
    <Paragraph position="0"> Lexical entries should not be either underspecified or overspecified. Unless the lexical phrases are fully specified, they cannot serve in disambiguation. On the other hand, overspecification should also be avoided. Indeed, in encoding lexicons there is a temptation to overspecify. Consider the following pairs of examples in regard to lexical constraints: He kicked the bucket.</Paragraph>
    <Paragraph position="1"> Mary was taken by the car dealer.</Paragraph>
    <Paragraph position="2"> He put his foot down.</Paragraph>
    <Paragraph position="3"> She laid down the law.</Paragraph>
    <Paragraph position="4"> He took on Goliath.</Paragraph>
    <Paragraph position="5"> The bucket was kicked.</Paragraph>
    <Paragraph position="6"> The car dealer took her.</Paragraph>
    <Paragraph position="7"> He put down his foot.</Paragraph>
    <Paragraph position="8"> She laid the law down.</Paragraph>
    <Paragraph position="9"> He took on him.</Paragraph>
    <Paragraph position="10"> There is a tendency to incorporate in the lexicon syntactic restrictions which will prevent the instances on the right. For example, kick the bucket would be marked as active-voice-only. This is in contrast to the phrase bury the hatchet which maintain its figurative flavor also in the passive voice: the hatchet was buried by Israel and Egypt.</Paragraph>
    <Paragraph position="11"> We believe that this behavior is not dictated by an 312 Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon arbitrary, ad hoc syntactic restriction, rather it reflects the conceptual representation of the phrase as it has been shaped in the acquisition process \[Zernik87b\]. The acquisition of the phrase bury the hatchet was based on a metaphor, and generalized from single-word meanings. Bury was generalized into disenable-use, and the referent the hatchet was generalized to a tool, the availability of which is a precondition for an active conflict. Therefore, the reference the hatchet stands for a certain generalized object. On the other hand, kick the bucket was learned as a whole chunk, since the underlying metaphor remained unresolved. Thus, the referent the bucket is maintained as a literal not associated with any concept. Due to this difference, there may arise a discourse function for passivizing bury the hatchet. However, since there is no referent for the bucket, there will never occur the need to passivize that phrase. Therefore, marking the phrase pattern as active-voice-only is redundant (albeit correct).</Paragraph>
    <Paragraph position="12"> Another issue is verb-modifier separation, i.e.: David took on Goliath vs. He took him on. How can the lexicon account for this separation phenomenon? A grossly overspecified rule claims that pronouns (and only pronouns) separate such two-word verbs. However, there are counterexamples such as: He took that ugly giant on.</Paragraph>
    <Paragraph position="13"> (where the separation is by a lengthy reference). Therefore the rule must be revised to relate the phenomenon to given and new references. A given, or an already resolved reference, can separate, while a new reference cannot be placed between the verb andits modifier. We believe that this behavior should not be specified by the lexicon, rather the generation decision is according to discourse functions.</Paragraph>
    <Paragraph position="14"> Overspecified lexical entries can always be contradicted by instances in context. In order to avoid the such contradictions we take the approach of maintaining syntactic specifications of lexical entries at appropriate levels, and use conceptual representation to account for apparently syntactic restrictions.</Paragraph>
  </Section>
  <Section position="12" start_page="0" end_page="0" type="metho">
    <SectionTitle>
3. LEXICAL REPRESENTATION: PREVIOUS WORK
</SectionTitle>
    <Paragraph position="0"> DHPL is a continuation of efforts in three distinct areas.</Paragraph>
    <Paragraph position="1"> First, in integrating the underlying situation as part of the lexical entry, we extend previous work on lexical presupposition. Second, we modify Wilensky's method of lexical representation for use in language acquisition.</Paragraph>
    <Paragraph position="2"> Third, we examine Bresnan's system of linguistic representation, which proves problematic in light of the acquisition task, and compare it to DHPL's representation. null presupposition of the utterance, is described by Keenan (1971) as follows*: The presuppositions of a sentence are those conditions that the world must meet in order for the sentence to make literal sense. Thus if some such condition is not met, for some sentence S, then either S makes no sense at all or else it is understood in some nonliteral way, for example as a joke or metaphor.</Paragraph>
    <Paragraph position="3"> Despite this definition of presupposition as a condition for application of lexical knowledge, presupposition has been studied as a means for generation and propagation of inferences, reversing its role as a condition. In \[Gazdar79, Karttunen79, Keenan71\] the goal has been to compute the part of the sentence which is already given, by applying &amp;quot;backward&amp;quot; reasoning, i.e.: from the sentence the king of France is bald determine if indeed there is a king in France, or from the sentence it was not John who broke the glass, determine whether somebody indeed broke the glass. Rather than using presuppositions to develop further inferences, we investigate how presuppositions are actually applied according to Keenan's definition above, namely, in determining appropriate utterance interpretations.</Paragraph>
    <Paragraph position="4"> Fillmore \[Fillmore78\] introduced lexical presupposition to describe situations in which lexical items may appear. He described the meanings of judgement words such as accuse, criticize, blame, and praise, by separating the entire meaning into (a) a statement (the illocutionary act), and (b) a presupposition. We illustrate this distinction by comparing the meanings of criticize and accuse in the following sentences:  (30) John criticized Mary for adjourning the meeting.</Paragraph>
    <Paragraph position="5"> (31) John accused Mary of adjourning the meeting.</Paragraph>
    <Paragraph position="6">  In both sentences, John referred to a hypothetical act, namely adjourning the meeting. In (30), it is presupposed that Mary committed the act (a test for determining presupposition is invariance under negation: John did not criticize Mary of adjourning the meeting still implies that Mary committed the act), while it is stated that the act is judged negatively. In (31), on the other hand, it is stated that Mary committed the act, while it is presupposed that the act is negative.</Paragraph>
    <Paragraph position="7"> We believe Fillmore's approach is suitable also for the task of language acquisition, since learning involves factoring out the statement of a phrase from the entire surrounding context. We have further pursued Fillmore's notion in utilizing lexical presupposition in specific tasks such as disambiguation, indexing, and accounting for communicative goals \[Gasser86a\].</Paragraph>
    <Paragraph position="8"> Presupposition must be distinguished from precondition. Consider the following text.</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
3.1 LEXICAL PRESUPPOSITION
</SectionTitle>
      <Paragraph position="0"> A message might be conveyed by an utterance beyond its straightforward illocution. That message, called the John ran into a pedestrian on a red light.</Paragraph>
      <Paragraph position="1"> He managed to explain it away in court.</Paragraph>
      <Paragraph position="2"> *(See also \[Grice75\] and \[Fauconnier85\] Ch. 3) Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 313 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon The lexical phrase under consideration is explain away.</Paragraph>
      <Paragraph position="3"> The presupposition for the application of the phrase is the entire situation in which the phrase typically appears. A person is attempting to justify a certain planning failure. The precondition for the enablement of the act, on the other hand, is a planning element from the domain itself. One precondition in the story above could be the judge's permission for John to stand up in court and defend his own case. Another trivial example is the sentence below.</Paragraph>
      <Paragraph position="4"> selection is by specificity, namely, the most specific phrase is selected.</Paragraph>
      <Paragraph position="5"> An additional layer was added to this work by Jacobs \[Jacobs85\] who noticed the need for inheritance and hierarchy in the lexicon. Concepts in memory are organized in a hierarchy of categories, through which more specific concepts can inherit features from more general ones. Concepts in the lexicon, namely lexical items, should be organized through the same general discipline. This approach enjoys three advantages: John threw a rock at Mary.</Paragraph>
      <Paragraph position="6"> There is no presupposition for the generic phrase person throw phys-obj. This phrase may appear in almost any context. However, from a planning point of view, for a person to throw a rock she must first grasp the rock in her hand. In contrast to presupposition, such planning information should not reside in the lexicon. In fact, any information which could be derived by means of general world knowledge does not belong in the lexicon.</Paragraph>
      <Paragraph position="7"> Dyer \[Dyer83\] has described text comprehension as an integrated cognitive process. Parsing, he claimed, cannot be separated from other cognitive tasks such as memory update and retrieval. Accordingly, search demons were introduced in lexical entries to perform memory retrieval. For example, consider the difference between the two sentences.</Paragraph>
      <Paragraph position="8"> (32) John made up his mind.</Paragraph>
      <Paragraph position="9"> (33) He decided to go swimming.</Paragraph>
      <Paragraph position="10"> In parsing sentence (33) the selected plan, namely going swimming, is mentioned explicitly. However, in sentence (32) neither the plan nor the problem to be resolved are mentioned explicitly. Therefore, a search demon associated with the phrase make up one' s mind is dispatched to retrieve from memory the problem under consideration by the actor of the phrase. One of the objectives of DHPL's representation is to eliminate such procedural knowledge. Lexical presupposition serves the task of memory retrieval. The mechanisms we use are unification and variable binding.</Paragraph>
    </Section>
    <Section position="2" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
3.2 LANGUAGE AS A KNOWLEDGE-BASED SYSTEM
</SectionTitle>
      <Paragraph position="0"> Wilensky \[Wilensky81\] promoted the view of language processing as a knowledge-based task. Accordingly, he suggested representing linguistic knowledge as a data-base of rules given at various levels of generality. The basic representation element is called a phrase, given as a pattern-concept pair. For example, the phrase in the  sentence: * Modularity: Adding a new entry does not require any global modification.</Paragraph>
      <Paragraph position="1"> * Declarativeness: The representation is neutral with respect to parsing and generation. The representation does not reflect any programming style (beyond basic slot-filler notation) and it does not reflect the mechanism of any particular parser.</Paragraph>
      <Paragraph position="2"> * Uniformity: Modifying the level of generality of a  phrase does not require a change of the phrase beyond the single feature being updated (generalized or specified).</Paragraph>
      <Paragraph position="3"> These properties make the system more amenable to modeling language processing \[Kay79\] and acquisition \[Mitchell82\].</Paragraph>
    </Section>
    <Section position="3" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
3.3 LFG AND LANGUAGE ACQUISITION
</SectionTitle>
      <Paragraph position="0"> Bresnan's \[Bresnan82a\] linguistic representation, lexicalfunctional grammar (LFG), is a system with a &amp;quot;flat&amp;quot; lexicon, which does not define a hierarchy of generalizations. LFG is contrasted here with DHPL's hierarchical approach, and it is examined here in regard to learning \[Pinker84\]. In LFG there are two lexical entries representing the word ask, as it appears in the following sentences.</Paragraph>
      <Paragraph position="1"> (34) John asked to leave.</Paragraph>
      <Paragraph position="2"> (35) John asked Mary to leave The corresponding lexical entries are given respectively  below.</Paragraph>
      <Paragraph position="3"> ask: v:pred = &amp;quot;ask(sub j, v-comp)&amp;quot; subj = v-comp's subj (subj-equi) ask: v:pred = &amp;quot;ask(sub j, obj, v-comp)&amp;quot; obj = v-comp's subj (obj-equi)  John dropped out of police academy.</Paragraph>
      <Paragraph position="4"> is given as the phrase pattern ?x:person drop out of ?y:school concept goal of person ?x, pursue-education at institute ?y, terminated unsuccessfully Parsing is viewed as a process of rule (phrase) application. When more than one rule is applicable (ambiguity), The meaning of ask is given as the predicate ask which takes either two or three arguments. There is no general notion which captures the similarities in the behavior of the two specific entries. In the hierarchical approach, on the other hand, the behavior of ask is described in the broader context of the infinitive interaction between phrases. The schematic hierarchy is given in Figure 2  below: 314 Computational Linguistics, Volume 13, Numbers 3-4, July.December 1987 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon P ! equi-rule /\ communication-verbs tell promise P2 ask planning-verbs  AI Capone went on trial.</Paragraph>
      <Paragraph position="5"> The judge threw the book at him.</Paragraph>
      <Paragraph position="6"> The underlying knowledge is the the trial script, which captures the basic events taking place in court.  (a) The Prosecutor communicates his arguments. (b) The Defendant communicates his arguments. (c) The Judge decides (select-plan) either: (1) Punish (thwart a goal of) Defendant.</Paragraph>
      <Paragraph position="7"> (2) Do not punish him.</Paragraph>
      <Paragraph position="8">  In this scheme, there is a single phrase for ask (P2). This phrase draws properties from a more general phrase (P1) which defines the general equi rule in complement-taking English verbs. In this representation, the behavior of ask is inherited from the general phrase P1 and there is no need to duplicate specificcases. LFG current theory does not facilitate such hierarchies. In absence of hierarchy and inheritance, there is a need for duplication of the learning effort which can lead to serious flaws in modeling human behavior. For example, the word promise presents an exception to the general equi rule. Consider John promised Mary to go, in contrast to John asked Mary %o go. The latter implies that John is the actor of the future act of going (John promised that he will go, but John asked that Mary go). In learning this behavior of promise, children make an error by hypothesizing the default equi rule, thus committing an error of overgeneralization (a child might say: Dad promised Tommy to drive the big car alone meaning &amp;quot;Tommy will drive the car&amp;quot;). In LFG it is impossible to model this behavior since generalizations do not exist. Indeed, Pinker \[Pinker84\] accounted for this error, but the equi rule he resorted to is not part of the LFG system itself. Moreover, through LFG it is impossible to recover from overgeneralization. Normally people recover from overgeneralizations by being given a counterexample (No. Dad promised Tommy to take him to Disneyland). However, since neither Bresnan nor Pinker attempt to represent meanings of words such as take and drive -- the meanings are actually represented as the symbols &amp;quot;take&amp;quot; and &amp;quot;drive&amp;quot; - it is impossible to make the necessary semantic inferences for error recovery. Thus, without the ability to generalize and without an appropriate representation of concepts, LFG as currently defined, cannot account for these behaviors in learning.</Paragraph>
      <Paragraph position="9"> This script, as shown in Figure 3, consists of a sequence of four events, in which the characters are the judge, the prosecutor, and a defendant. In addition, there is knowledge of the character's goals. The prosecutor is interested in thwarting a preservation goal - p-freedom, p-property of the defendant. The defendant attempts to block this goal thwart. Both parties advance their cases by trying to convince the judge. By this representation the meaning of the phrase to throw the book at somebody means to punish him severely, based on events (a) and (1) in the script.</Paragraph>
      <Paragraph position="10"> Another situation, involving the same script, is presented in the following text.</Paragraph>
      <Paragraph position="11"> John ran over a pedestrian.</Paragraph>
      <Paragraph position="12"> He failed to explain it away in court, and he went to jail In this case the phrase explain away pertains to the underlying goal-plan situation, given in Figure 4 below.</Paragraph>
    </Section>
  </Section>
  <Section position="13" start_page="0" end_page="0" type="metho">
    <SectionTitle>
4. REPRESENTING THE CONTEXT
</SectionTitle>
    <Paragraph position="0"> The semantics of entries in the lexicon draw from the various contexts in which they have been applied. Here we represent contexts using scripts, plans, goals, and relationships \[Schank77, Dyer83, Dyer86b\]. Consider the context in reading the text: ing safely). John's preservation goal of freedom is threatened. A plan for preserving this goal is convincing the judge as to why John himself was not at fault. This second plan is executed and it fails also. Thus, his p-goal fails.</Paragraph>
    <Paragraph position="1"> Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 315 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon. Notice that the same goal-plan schema exists also in the case of the next story: Joe forgot to put away the dirty dishes.</Paragraph>
    <Paragraph position="2"> When his wife came home, he argued it away by telling her he had been working.</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
5.1 BASIC PHRASE STRUCTURE
</SectionTitle>
      <Paragraph position="0"> Consider the marked clause in the following text.</Paragraph>
      <Paragraph position="1"> For years they tried to prosecute A1 Capone.</Paragraph>
      <Paragraph position="2"> Finally, a judge threw the book at him for income-tax evasion.</Paragraph>
      <Paragraph position="3"> The phrase argue away also involves a prior plan failure, a thwarted p-goal (p-social-relation) and a recovery plan of convincing the other party. This underlying schema is a presupposition. It holds whether Joe fails to argue it away or whether he manages to argue it away. Since the same plan-goal schema underlies both phrases (up to the specific plan: argue vs. explain), they both can be viewed as instances of a more general phrase.</Paragraph>
      <Paragraph position="4"> Many other phrases draw their meanings in terms of such general plan-goal structures. Consider the phrases in the next sentences: This machine was idling away for hours.</Paragraph>
      <Paragraph position="5"> They stayed at home, and argued away for hours.</Paragraph>
      <Paragraph position="6"> The class was boring. John sat near the window dreaming away.</Paragraph>
      <Paragraph position="7"> In all these sentences there is a similar underlying situation, shown in Figure 5 below.</Paragraph>
      <Paragraph position="8"> play work .~ _ dream number cruncA .v. I echieve ~onlllCt~/ achieve  In this schema a resource competition (the resource is time) exists for an agent between two competing tasks, and that agent subordinates the important goal. The fact that phrase representation can be elevated to a level of general plans and goals is very significant. It implies that a relatively small number of structures can represent phrases whose instances can be used across many domains.</Paragraph>
      <Paragraph position="9"> This clause is derived from a lexical phrase which is given as the following simplified template: phrase pattern: presupposition: concept: Personl throw the book at Person2.</Paragraph>
      <Paragraph position="10"> Personl is an authority for Person2.</Paragraph>
      <Paragraph position="11"> Personl punishes person2 severely.</Paragraph>
      <Paragraph position="12"> This lexical phrase is a triple associating a linguistic pattern with its semantic concept and presupposition. The pattern specifies the syntactic appearance in text. The presupposition specifies the surrounding context, while the concept specifies the meaning added by the phrase itself. Phrase presupposition, distinguished from phrase concept, is introduced in DHPL's representation since it solves three problems: (a) in disambiguation it provides a discrimination condition for phrase selection, (b) in acquisition it allows the incorporation Of the context of the example as part of the phrase, and (c) in generation it provides an indexing scheme for phrase discrimination and triggering.</Paragraph>
      <Paragraph position="13"> The role of the three slots in a phrase template may be better understood by the way they are applied in parsing the text above. The clause is parsed in four steps:  (1) The pattern is matched successfully against the text. Consequently, Personl and Person2 are bound to the judge and to AI Capone respectively (as the person class restrictions imposed by the pattern are satisfied).</Paragraph>
      <Paragraph position="14"> (2) The presupposition associated with the pattern is validated using the concepts in the context. Using knowledge of human relationships, it is inferred that the judge presents an authority to Capone. (3) Since both (1) and (2) are successful, then the  pattern itself is instantiated, adding to the context: The judge punished At Capone severly.</Paragraph>
      <Paragraph position="15"> (4) Steps (1)-(3) are repeated for each relevant lexical entry. If more than one entry is instantiated, then the concept with the best match is selected.</Paragraph>
    </Section>
  </Section>
  <Section position="14" start_page="0" end_page="0" type="metho">
    <SectionTitle>
5. ORGANIZING THE LEXICON
</SectionTitle>
    <Paragraph position="0"> Retrieval and update are the operations required of memory \[Kolodner84\], and of the lexicon in particular.</Paragraph>
    <Paragraph position="1"> The objective in DHPL is to retrieve lexical entries at various levels of generality. The structure of the lexicon is specified by (a) the structure of a single lexical element, and (b) the global structure in which elements are organized.</Paragraph>
  </Section>
  <Section position="15" start_page="0" end_page="0" type="metho">
    <SectionTitle>
(1) ACTUAL SLOT-FILLER NOTATION
</SectionTitle>
    <Paragraph position="0"> The actual representation of the phrase is implemented using GATE's \[Mueller87\] slot-filler language, as shown below. In particular notice in that notation that the representation of a phrase, which is a linguistic object, is not different than the representation of other objects in the database.</Paragraph>
    <Paragraph position="1">  Notice that the phrase consists of three main parts: pattern, concept and presupposition (the comment is for reference only).</Paragraph>
  </Section>
  <Section position="16" start_page="0" end_page="0" type="metho">
    <SectionTitle>
(2) CASE-FRAME REPRESENTATION
</SectionTitle>
    <Paragraph position="0"> The pattern of the phrase above can be written as: ?x throw &lt;the book&gt; &lt;at ?y&gt; This is an abbreviation which stands for the full notation given below.</Paragraph>
    <Paragraph position="1">  This case is referred to as the lexical subject to be distinguished from the surface subject (the element actually preceding the verb in the text).  (3) Case frames are unordered, namely no order is  imposed among the case frames. In no place in the case frame is it mentioned, for example, that the lexical subject should precede the verb or follow it (or not appear at all). Case ordering, thus, is inherited from general linguistic patterns, as shown  later in this paper.</Paragraph>
    <Paragraph position="2"> (4) Case frames contain both semantic and syntactic  properties. For example, objectl defines the named constituents the and book, while object2 defines the class person.</Paragraph>
    <Paragraph position="3"> Since not all properties are given explicitly within the pattern itself, there is a need for an inheritance scheme. Properties such as case order (e.g. active and passive voice), and word-order of the syntactic constituents within cases (e.g. the determiner the precedes the root book) are inherited from general linguistic patterns.</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
5.2 THE GLOBAL STRUCTURE
</SectionTitle>
      <Paragraph position="0"> While varying in generality, lexical entries are represented uniformly throughout. The lexicon can be viewed as a collection of triples (Pattern-Concept-Presupposition), as shown in Figure 7, which are retrieved for parsing and for generation tasks, and become operational by unification.</Paragraph>
      <Paragraph position="1"> throw the book explain away (i~&amp;quot; ~ exolain  To facilitate learning, these triples are organized in hierarchies by generality. In a hierarchical scheme, the bottom nodes are very specific and idiomatic while the ones at the top are more general. Phrases may reside at, and inherit from, more than one hierarchy. For example, the phrase to take on can inherit from the hierarchy of take as well as from the hierarchy of on (a hierarchy which defines properties of verb modifiers). Four operations, implemented as forms of unification, and are defined by this representation. They are: (a) interaction between two unrelated phrases, (b) inheritance between two related phrases (one more general than the other),  (c) generalization, and (d) discrimination of a phrase, which both update its level of generality. Three hierarchy schemes are given in the following sections to demonstrate three aspects of the system: (a) phrase interaction through the infinitive construction, (b) word-sense representation, and (c) case-order.</Paragraph>
      <Paragraph position="2"> 6. REPRESENTING THE INFINITIVE  Consider the following pair of clauses in the sentences below: Judge Wilson threw the book at him.</Paragraph>
      <Paragraph position="3"> Judge Wilson decided to throw the book at him.</Paragraph>
      <Paragraph position="4"> Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 317 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon Parsing the first sentence is carried out simply as a lexicon lookup: a phrase is found in the lexicon, and its concept is instantiated. Parsing the second sentence is more complex since no single lexical phrase is matched for throw. For one thing, the subject does not precede the verb throw as anticipated by the lexical pattern.</Paragraph>
      <Paragraph position="5"> Identifying the implicit subject involves knowledge of phrase interaction. Properties of phrase interaction (through the infinitive form \[Kiparsky71\]) are represented by a hierarchy below.</Paragraph>
      <Paragraph position="6">  The names of the individual nodes are mnemonic, and are used for reference only. Each such node is a full pattern-concept-presupposition triple (the presupposition may not appear). The nodes in Figure 8 are described as follows: (a) The most general node (P1) denotes the basic equi rule, which stands for the following object: comment the general equi behavior  In this phrase, notice in particular the complement (comp), which defines the embedded phrase. The implicit subject of the embedded phrase is taken as either (1) the object of the embedding phrase, if that object exists, or (2) the subject of the embedding phrase, if the object does not exist.</Paragraph>
      <Paragraph position="7"> (b) Middle-level nodes encompass classes of verbs.</Paragraph>
      <Paragraph position="8"> For example, P2 encompasses communication verbs such as ask, tell, instruct, etc., share certain features. It is represented as follows:  This phrase is similar to the phrase P1. However, it includes information specific to that class of verbs. It defines shared syntactic features: subject, verb, object, complement (where the complemen- null tizer is to). It also defines shared semantic properties: (a) the equi-rule, (b) the concept of the complement, which is a hypothetical, future plan communicated by the actor.</Paragraph>
      <Paragraph position="9"> (c) Specific nodes give the behavior of individual verbs, such as the phrases for decide (a planning verb) and command (a communication verb).</Paragraph>
      <Paragraph position="10"> comment X decide to Z pattern (subject instance ?x) (verb  (d) Episodes such as P4, which include specific instances of a phrase, are indexed to the phrase. For example, P4 is the situation in which God commands Moses to approach the Mountain. This episode contains the semantic ingredients constituting the meaning of the phrase.</Paragraph>
      <Paragraph position="11"> The hierarchy of Figure 8 is used by four processing tasks.</Paragraph>
    </Section>
    <Section position="2" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
6.1 PHRASE INTERACTION
</SectionTitle>
      <Paragraph position="0"> The analysis of the sentence below: Judge Wilson decided to throw the book at him. involves the interaction of two specific phrases, as shown schematically in Figure 9. The two specific lexical phrases involved are the entries for decide (the embedding phrase, P1, elaborated in item (c) at the beginning of Section 6 above) and for throw the book (the embedded phrase, P2, described in Figure 6 above). The unification of these two phrases guarantees that: (a) the subject of P1 is the subject of P2, and (b) the concept of the P2 (denoted by ?z) is plugged in the plan slot of P1. The interaction of these two phrases yields the compound concept:</Paragraph>
      <Paragraph position="2"> This concept conveys the meaning of the entire sentence. null</Paragraph>
    </Section>
    <Section position="3" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
6.2 PARSING AN UNKNOWN
</SectionTitle>
      <Paragraph position="0"> In contrast to the previous example, consider the analysis of a sentence in which an unknown word is Mary goggled John to come over.</Paragraph>
      <Paragraph position="1"> In analyzing this sentence, no lexical phrase is found to account for the word goggle. Therefore, the meaning of the entire sentence cannot be produced. Yet, even a partial meaning cannot be produced for the known clause, to come over, since it is intertwined with the unknown clause Mary goggled John. In order to overcome this obstacle, the interaction involves a more general phrase as shown in Figure 10. In contrast to Figure 9, here no specific phrase could be found for goggze, and it is necessary to select the generalized phrase, P1, which encompasses communication verbs in general. For come over, on the other hand, there exists a specific entry in the lexicon, P2, thus a generalization is not sought for. The partial meaning constructed for the sentence, in absence of a phrase for goggle is:</Paragraph>
      <Paragraph position="3"> Thus, even when the particular phrase does not exist, the parser is able to construct an initial hypothesis, based on a generalization.</Paragraph>
      <Paragraph position="4"> In fact, the selection of the generalized phrase is not unambiguous. The nature of the selected phrase is restricted by two schemes: (a) the hierarchy in Figure 8 above, and (b) the persuade plan box \[Schank77\] which provides the planning options available for a person in persuading another person to act (overpower, threaten, promise, steal, etc.). Accordingly, goggle could have as well conveyed meanings such as:  (36) Mary pushed John to come over. (influence verb) (37) Mary let John come over. (help verb) (38) Mary threatened John to come over. (promise verb)  Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 319 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon Indeed option (38) is not available in English, however, since the phrase is yet unknown to the learner, this option must be given consideration.</Paragraph>
    </Section>
  </Section>
  <Section position="17" start_page="0" end_page="0" type="metho">
    <SectionTitle>
6.30VERGENERALIZATION AND RECOVERY
</SectionTitle>
    <Paragraph position="0"> In the case that the word promise does not exist in the lexicon, the program behaves as follows: User: John promised Mary to come over.</Paragraph>
    <Paragraph position="1"> RINA: John told Mary that she must/can come to him.</Paragraph>
    <Paragraph position="2"> In using the generalized phrase, RINA unified inappropriately the roles. This is an error of overgeneralization which is typical of children learning new vocabulary items.</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
6.4 ERROR RECOVERY
</SectionTitle>
      <Paragraph position="0"> The user can correct the program by giving an explicit example.</Paragraph>
      <Paragraph position="1"> User: No. John promised Mary to come to her place. By using few inferences (e.g., person ?x does not come to the same person ?x), RINA figures out the confusion in the role-binding and corrects appropriately the phrase for promise, as given below: comment X promise Y to Z  subject of the embedded phrase, and (b) the act ?z is presupposed to be a goal of ?y. ?x is the subject of the embedded act, and the act ?z is presupposed to be a goal of ?y.</Paragraph>
    </Section>
  </Section>
  <Section position="18" start_page="0" end_page="0" type="metho">
    <SectionTitle>
7. HANDLING WORD SENSES
</SectionTitle>
    <Paragraph position="0"> By its nature, the phrasal approach is oriented towards the representation of entire groups of words. However, single words, such as up, at, and away must also be represented. Three issues are involved in representing such words.</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
7.1 ASSIGNING MEANINGS TO PARTICLES
</SectionTitle>
      <Paragraph position="0"> Compare the following two sentences: (39) John looked up at Mary.</Paragraph>
      <Paragraph position="1"> (40) John looked at Mary.</Paragraph>
      <Paragraph position="2"> The meanings of the two sentences are given below*: (39) (40) attend attend object eyes object eyes actor john.3 actor john.3 to mary.4 to mary.4 direction vertical-positive The contribution of the particle up is given as (direction vertical-positive). The role of the particle in the next sentence is less obvious.</Paragraph>
      <Paragraph position="3"> (41) John flew away from the scene of the crime. What is the contribution of the word away to the meaning of sentence (41)? For instance, how is the meaning of sentence (41) different than the meaning of sentence (42) below?  (42) John flew to Alaska.</Paragraph>
      <Paragraph position="4"> 7.2 RESOLVING WORD-SENSE AMBIGUITY Is the contribution of away identical in all the sentences (43)-(46), or are there several meanings involved? (43) John flew away from the scene of the crime. (44) John did not put away the clean dishes. (45) He managed to argue it away with his wife. (46) This machine was idling away for hours.  For example, consider two appearances of the production argue away which involve two different senses of away: (47) His lawyer can argue away any tax violation. (48) He is a bum. He can argue away for hours without convincing anybody.</Paragraph>
      <Paragraph position="5"> The first sense implies success in deceiving the authorities (as in get away with), while the second sense implies a waste of time (as in idle away). If there is more than one sense for away, then how is the appropriate meaning selected in each instance? In our lexicon, there are two phrases for argue away, which are disambiguated by matching their presuppositions with the context. The two phrases are: *Another phrase, John looked up to Mary, in contrast to John looked up at Mary, is not processed as a simple production of the particles, since it involves the entire phrase &amp;quot;X look up to Y&amp;quot;. 320 Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon pattern ?x ( ?v away ) ?y presupposition ?y is a planning failure by ?x ?g is ?x's goal thwarted by authority punishment ?z ?v is a communication act by ?x to avert ?z concept act ?v is successful, and ?z is averted pattern ?x ( ?v away ) presupposition act ?v serves no goal of ?x act ?v consumes a useful resource (time) concept act ?v is selected by ?x Figure lh Two Different Senses for argue away The appropriate phrase is selected in each context by matching the presupposition.</Paragraph>
    </Section>
    <Section position="2" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
7.3 DETERMINING LEVEL OF GENERALITY
</SectionTitle>
      <Paragraph position="0"> Which is the appropriate alternative for representing the phrase in sentence (49)?  (49) He managed to argue it away with his wife. (a) Is it as &amp;quot;fixed&amp;quot; phrase as given below? (b)  pattern: ?x away ?y ?z concept: ?x managed to explain event ?y to person ?z by arguing.</Paragraph>
      <Paragraph position="1"> Or is it a &amp;quot;variable&amp;quot; phrase as given next: pattern: ?x away ?y concept: ?x managed to explain event ?y to person ?z by act ?v.</Paragraph>
      <Paragraph position="2"> Answers for these dilemmas are given by the hierarchy in Figure 12 below: (a) The most general phrase (P1) denotes the general properties of English verb modifiers. The modifier follows the verb, but separation is allowed (i.e.: he explained it away VS. he explained away his latest goo f).</Paragraph>
      <Paragraph position="3"> P ! verb modifier  ing conveyed by words such as away (P2), up and down. The pattern for P2, for example is &lt;?v away&gt; where ?v can be any verb.</Paragraph>
      <Paragraph position="4"> (c) Nodes at the third level convey word senses which encompass classes of specific phrases. For example, P3a (convince) conveys the meaning encompassing both explain it away and argue it away, while P3b (waste time) conveys the meaning encompassing both idle away and sing away. These two phrases (P3a and P3b) are elaborated here: pattern ?x ( argue away ) ?y presupposition ?y is a planning failure by ?x ?g is ?x's goal thwarted by authority punishment ?z ?v (argue) is a communication act by ?x to avert ?z concept act ?v (arguing) is successful, and ?z is averted pattern ?x ( argue away ) presupposition act ?v (arguing) serves no goal of ?x act ?v consumes a useful resource (time) concept act ?v (arguing) is selected by ?x These two phrases generalize respectively the phrases in Figure 11.</Paragraph>
      <Paragraph position="5"> (d) Nodes at the next level denote specific phrases, or productions, such as run away, argue away (P4), idle away, etc. Such phrases are given in Figure 11 for two cases of argue away.</Paragraph>
      <Paragraph position="6"> (e) Nodes at the bottom level describe episodes in which instances of phrases were encountered (e.g., the instances A1 Capone argued it away in court (P5), John Smith argued it away with his wife are indexed to the phrase &lt;?x argue ?y away&gt;). On the face of it, it seems that levels (a) and (d) are sufficient for all parsing and generation purposes. What is the function of levels (b), (c), and (e)?</Paragraph>
    </Section>
    <Section position="3" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
7.4 ANALYZING A NEW PRODUCTION
</SectionTitle>
      <Paragraph position="0"> These intermediate levels of generalization facilitate the analysis of new productions such as: (50) John tried to describe it away in court.</Paragraph>
      <Paragraph position="1"> Sentence (50) introduces a new production to the reader of this paper. Yet, the reader should be able to resolve the new production by using the generalized linguistic pattern P3a in Figure 12.</Paragraph>
    </Section>
  </Section>
  <Section position="19" start_page="0" end_page="0" type="metho">
    <SectionTitle>
7.5 LEARNING FROM EXAMPLES
</SectionTitle>
    <Paragraph position="0"> In the previous example we have assumed an existing generalized phrase P3a, which was used in predicting a specific phrase. When such a generality does not exist, learning must be done by induction from specific examples. The following set of examples provide episodes Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 321 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon from which RINA can hypothesize the meaning of the phrase to take on.</Paragraph>
    <Paragraph position="1"> altogether? This information is contained in a case-order hierarchy (Figure 14 below) in the lexicon.</Paragraph>
    <Paragraph position="2">  (51) David took on Goliath.</Paragraph>
    <Paragraph position="3"> (52) The Celtics took on the Lakers.</Paragraph>
    <Paragraph position="4"> (53) Finally, I took on the hardest question  on the midterm.</Paragraph>
    <Paragraph position="5"> So far we have shown two ways of deriving new phrases: First, a new phrase can be generalized from indexed episodes (which include instances in context). However, learning is easier when a generalized template already exists, in which case learning is accomplished by applying a generality \[Zernik85a\].  The patterns for the passive and the active voice, for example, are given in the figure below.</Paragraph>
    <Paragraph position="6"> P2: subject (location bef) (marker none)  away is deduced top-down from an existing general concept (P3a). On the other hand, take on is induced bottom-up from the set of specific episodes such as David and Goliath, the Celtics vs. the Lakers, and the midterm. There is no generalized concept which could serve as a short cut.</Paragraph>
    <Paragraph position="7"> In matching sentences (54) and (55) above, the pattern P0 inherits case-order properties from these general linguistic patterns. For example, after inheriting the passive voice for matching sentence (55), the pattern augmented by inheritance from P3 would be: PI: subject (location aft) (marker by) (class person) verb (location ref) (voice passive) (root throw) object1 (location bef)(marker none) (root book) object2 (location aft) (marker at) (class person)</Paragraph>
  </Section>
  <Section position="20" start_page="0" end_page="0" type="metho">
    <SectionTitle>
8. INHERITING CASE ORDER
</SectionTitle>
    <Paragraph position="0"> Consider the lexical pattern given as a set of four unordered case-frames: An even more general pattern exists which captures the basic SVO structure of the language. This phrase is given at the top of the hierarchy:  PO: ?y throw &lt; book&gt; &lt;at ?x&gt; Since ordering is not specified explicitly in pattern P0, then how can this pattern match sentences such as: (54) The judge threw the book at AI. (active voice) (55) The book was thrown at him. (passive voice) (56) AI he decided to throw the book at, but John he gave a break. (left dislocation) (57) &amp;quot;Take it easy!&amp;quot; said the prosecutor. (right dislocation) Under what condition does the lexical subject precede the verb, and when can the lexical subject be omitted  Mary was fed by John.</Paragraph>
    <Paragraph position="1"> as if Mary actually fed John. Adults too, in case of missing knowledge, might resort to this generality in making sense out of sentences.</Paragraph>
    <Paragraph position="2"> 9. FIGURATIVE PHRASE ACQUISITION: A PROCESS MODEL So far, we have assumed the existence of necessary phrases in the lexicon. However, in reality a program may encounter new phrases in the text. Thus, the program must accomplish two objectives: (a) parse the text in spite of the unknown element, and (b) acquire information about the unknown element for future encounters. Consider the situation in which the figurative phrase is first encountered.</Paragraph>
    <Paragraph position="3"> User: The mobster eluded prosecution for years. Last month, they threw the book at him for income-tax evasion.</Paragraph>
    <Paragraph position="4"> RINA: The prosecutor propelled a book at him? User: No. A judge threw the book at him.</Paragraph>
    <Paragraph position="5"> RINA: The judge threw the book at him. He found him guilty.</Paragraph>
    <Paragraph position="6"> And later on: User: The dean of the school threw the book at John. RINA: He punished him.</Paragraph>
    <Paragraph position="7"> There are three stages in the acquisition process:  (1) Apply the literal interpretation.</Paragraph>
    <Paragraph position="8"> (2) Acquire the figurative phrase.</Paragraph>
    <Paragraph position="9"> (3) Generalize the new phrase beyond the specific context.</Paragraph>
  </Section>
  <Section position="21" start_page="0" end_page="0" type="metho">
    <SectionTitle>
9.1 LITERAL INTERPRETATION
</SectionTitle>
    <Paragraph position="0"> In the absence of the appropriate phrase in the lexicon, RINA utilizes other available knowledge sources, namely (a) the literal interpretation and (b) the context.</Paragraph>
    <Paragraph position="1"> The literal interpretation is given by the phrase:</Paragraph>
    <Section position="1" start_page="0" end_page="0" type="sub_section">
      <SectionTitle>
9.2 LEARNING BY FEATURE EXTRACTION
</SectionTitle>
      <Paragraph position="0"> In constructing the new hypothesis, the program must extract the relevant features from the given episode.</Paragraph>
      <Paragraph position="1"> (a) The initial phrase presupposition is taken to be the entire trial script.</Paragraph>
      <Paragraph position="2">  (b) The pattern is extracted from the sample sentence. (c) The concept is extracted from the script.  In extracting either the pattern or the concept, the problem is to distinguish between features which are relevant and should be taken in as part of the phrase, and features which are irrelevant and thus should be left out. Moreover, some features should be taken as is, where other features must be abstracted before they can be incorporated.</Paragraph>
    </Section>
  </Section>
  <Section position="22" start_page="0" end_page="0" type="metho">
    <SectionTitle>
9.3 FORMING THE PATTERN
</SectionTitle>
    <Paragraph position="0"> Four rules are used in extracting the linguistic pattern from the sentence: Last month, they threw the book at him for income-tax evasion.</Paragraph>
    <Paragraph position="1"> (1) Initially, use an existing literal pattern. In this case, the initial pattern is: patternl: ?x:person throw: ?z:phys-obj &lt;at ?y:person&gt;  Examine other cases in the sample sentence, and include cases in the pattern which could not be interpreted by general interpretation. There are two such cases: Last month could be interpreted as a general time adverb (i.e.: last year he was still enrolled at UCLA, the vacation started last week, etc.). For income-tax evasion can be interpreted as a element-paid-for adverb (i.e.: he paid dearly for his crime, he was sentenced for a murder he did not commit, etc.).</Paragraph>
    <Paragraph position="2"> This phrase describes propelling an object in order to hit another person. Notice that no presupposition is specified. General phrases such as take, give, catch, and throw do not have a expressed presupposition since they can be applied in many situations.* The literal interpretation fails by plan/goal analysis. In the context laid down by the first phrase (prosecution has active-goal to punish the criminal), &amp;quot;propelling a book&amp;quot; does not serve the prosecution's goals. In spite of the discrepancy, RINA spells out that interpretation above with a question mark, The prosecutor propelled a book at him.'? to notify the user about her current state of (3) Thus, both these cases are excluded.</Paragraph>
    <Paragraph position="3"> Variablize references which can be instantiated in the context. In this case ?x is the Judge and ?y is the Defendant. They are maintained as variables, as opposed to case (4): (4) Freeze references which cannot be instantiated in * Notice the distinction between preconditions and presupposition. While a precondition for &amp;quot;throwing a ball&amp;quot; is &amp;quot;first holding it&amp;quot;, this is not part of the phrase presupposition. Conditions which are implied by common sense or world knowledge do not belong in the lexicon. Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 323 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon the context: Since no referent is found for the reference the book, that reference is taken as a frozen part of the pattern instead of the case ?z:phys-obj.</Paragraph>
    <Paragraph position="4"> The resulting pattern is: pattern2: ?x:person throw: &lt;the book&gt; &lt;at ?y:person&gt;</Paragraph>
  </Section>
  <Section position="23" start_page="0" end_page="0" type="metho">
    <SectionTitle>
9.4 FORMING THE CONCEPT
</SectionTitle>
    <Paragraph position="0"> In selecting the concept of the phrase, there are four possibilities, namely the events shown in Figure 3 (Section 4). The choice of the appropriate one among these four events is facilitated by linguistic clues. As opposed to the phrase they threw the book to him which implies cooperation between the characters, the phrase they threw the book at him implies a goal conflict between the characters. At implies not taking acknowledgement protocols into consideration. E.g., x throws the rock to y implies that x catches y's attention, and gets acknowledgement for y's receipt of the rock. On the other hand, x throws the rock at y implies that y may not be aware or ready to receive the rock. This analysis applies also to talk at vs. talk to, etc. Since this property is shared among many verbs, it is encoded in the lexicon as a general phrase: pattern ?x:person ?v:verb ?y:phys-obj ( at ?y ) concept propel actor ?x  Notice that rather than having a specific root, the pattern of this phrase leaves out the root of the verb as a variable. From lack of acknowledgement, a goal conflict may be inferred.</Paragraph>
    <Paragraph position="1"> goal class p-health status thwarted goal-of ?z Using this concept as a search pattern, the &amp;quot;punishment-decision&amp;quot; is selected from $trial. Thus, the phrase acquired so far is: pattern ?x:person throw ( the book ) ( at ?y ) concept auth-punish actor ?x</Paragraph>
  </Section>
  <Section position="24" start_page="0" end_page="0" type="metho">
    <SectionTitle>
9.5 PHRASE GENERALIZATION
</SectionTitle>
    <Paragraph position="0"> Although RINA has acquired the phrase in a specific context, she might hear the phrase in a different context. She should be able to transfer the phrase across specific contexts by generalization. RINA generalizes phrase meanings by analogical mapping. Thus, when hearing the sentence below, an analogy is found between the two contexts.</Paragraph>
    <Paragraph position="1"> The third time he caught John cheating in an exam, the professor threw the book at him.</Paragraph>
    <Paragraph position="2"> The trial-script is indexed to a general authority relationship. The actions in a trial are explained by the existence of that relationship. For example, by saying something to the Judge, the Defendant does not dictate the outcome of the situation. He merely informs the Judge with some facts in order to influence the verdict. On the other hand, by his decision, the Judge does determine the outcome of the situation since he presents an authority. Three similarities are found between the $trial and the scene involving John and the professor.</Paragraph>
    <Paragraph position="3">  (a) The authority relationship between ?x and ?y.</Paragraph>
    <Paragraph position="4"> (b) A law-violation by ?y.</Paragraph>
    <Paragraph position="5"> (c) A decision by ?x.</Paragraph>
    <Paragraph position="6">  Therefore, the phrase presupposition is generalized from the specific trial-script into the general authoritydecree situation which encompasses both examples.</Paragraph>
  </Section>
  <Section position="25" start_page="0" end_page="0" type="metho">
    <SectionTitle>
10. CURRENT STATUS AND LIMITATIONS
</SectionTitle>
    <Paragraph position="0"> The lexical theory (DHPL) described in this paper underlies the program RINA described in the first author's dissertation \[Zernik87c\]. The program RINA is currently implemented in T \[Rees84\] (a dialect of SCHEME), on an APOLLO workstation using GATE's \[Mueller87\] unification language. RINA's lexicon includes more than 200 phrases including grammatic forms, word senses, and idioms. A &amp;quot;micro&amp;quot; version of the program, which carries out basic parsing and learning functions is included as an appendix of the dissertation \[Zernik87c\]. RINA can engage in learning sessions by using a variety of learning strategies. However, RINA's performance is limited in four ways.</Paragraph>
    <Paragraph position="1"> (1) Only fragments of the English grammar have been implemented in the current version of DHPL.</Paragraph>
    <Paragraph position="2"> More work is required for extending systematically the set of constructs handled by DHPL.</Paragraph>
    <Paragraph position="3"> (2) Text generation has not been at the focus of our work, and RINA's generation capabilities need to be enhanced.</Paragraph>
    <Paragraph position="4"> (3) Aspects of discourse and dialog have been accounted for by simple heuristics. The input/output dialogs of the program are restricted to a small number of examples.</Paragraph>
    <Paragraph position="5"> (4) Transfer plays a major role in second-language acqisition, as elements in language I are manifested 324 Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon in performing in language II. Accordingly, multiple languages in one model must not be represented in isolation. The aspect of transfer and cross-linguistic interference is modeled by Michael Gasser \[Gasser86b\].</Paragraph>
  </Section>
  <Section position="26" start_page="0" end_page="0" type="metho">
    <SectionTitle>
11. FUTURE WORK
</SectionTitle>
    <Paragraph position="0"> Open research issues are (a) generation of examples, (b) learning and forgetting, (c) concept generalization, and (d) handling irony.</Paragraph>
  </Section>
  <Section position="27" start_page="0" end_page="0" type="metho">
    <SectionTitle>
ll.1 GENERATION OF EXAMPLES
</SectionTitle>
    <Paragraph position="0"> We have identified a difference between generation tasks in general, where the generator describes a state of affairs in the world, and our specific task of example generation. In example generation, the program is required to demonstrate its own state of knowledge. For instance, one dialog given earlier proceeds as follows: User: Greg wanted to buy a new car.</Paragraph>
    <Paragraph position="1"> He took it up with his dad.</Paragraph>
    <Paragraph position="2"> RINA: He took up the car with his dad? The explicit reference the car is important since it conveys RINA's failure in acquiring the phrase. How could a program decide to generate the car (and not it) in contrast to he (and not Greg)? The research issue is: how a program or a person can test out its notion of a phrase. Examples must be generated to examine the boundary conditions in which the phrase can still be applied. This issue has not been investigated so far.</Paragraph>
  </Section>
  <Section position="28" start_page="0" end_page="0" type="metho">
    <SectionTitle>
11.2 LEARNING AND FORGETTING
</SectionTitle>
    <Paragraph position="0"> Two related issues are system stability and obsolescence, or forgetting. Stability concerns the ease with which well-established knowledge can be modified. If the behavior of the program is too dynamic, then it might easily get thrown off by one esoteric, or incorrect use of a phrase. It is not desirable that an adult native speaker would get his lexicon ruined by listening to a second language speaker. Forgetting involves inaccessibility of unused phrases, or getting rid of incorrect hypotheses. Are incorrect hypotheses simply destroyed, or is there a more realistic model of obsolescence? These two issues involve quantitative reasoning which require implementation of strength of links and activation. These kind of problems demonstrate the limitations of a strictly qualitative approach, such as ours, which rely on manipulation of logical propositions, and it raises the need for quantitative approaches such as connectionism \[Waltz85, McClelland86\], and spreading activation \[Anderson84, Charniak83\].</Paragraph>
  </Section>
  <Section position="29" start_page="0" end_page="0" type="metho">
    <SectionTitle>
11.3 CONCEPT GENERALIZATION
</SectionTitle>
    <Paragraph position="0"> Proliferation of knowledge is the process we try to approximate. The ubiquitous dilemma in comparing two concepts is whether a generalization exists for both, or whether they are distinct concepts. For example, consider the following sequence of examples in teaching the phrase to take on.</Paragraph>
    <Paragraph position="1">  (57) David took on Goliath.</Paragraph>
    <Paragraph position="2"> (58) I took on my elder brother.</Paragraph>
    <Paragraph position="3"> (59) I took on a new job.</Paragraph>
    <Paragraph position="4"> (60) We took on a new systems programmer.</Paragraph>
    <Paragraph position="5"> (61) This piece of paper took on the shape of a  butterfly.</Paragraph>
    <Paragraph position="6"> The second phrase can share the concept acquired for the first one, namely ?x decided to fight ?y. The third phrase; however, requires one to generalize the initial notion since it now appears as ?x accepted a challenge presented by ?y. However, can a generalization be found to encompass the fourth phrase? Notice that although a very general concept which encompasses all of the given examples could be found (?x has something to do with ?y), however, the effectiveness of such a generalized notion is totally diminished. Therefore, a shared concept should be sought at the appropriate level of generality.</Paragraph>
  </Section>
  <Section position="30" start_page="0" end_page="0" type="metho">
    <SectionTitle>
11.4 DEVIATIONAL USES OF LANGUAGE
</SectionTitle>
    <Paragraph position="0"> So far, the notion of lexical presupposition has not been developed according to its agreed functional definition.</Paragraph>
    <Paragraph position="1"> It is agreed that lexical presupposition presents felicity conditions for phrase application. When these conditions are violated, phrases sound awkward, ironic, or simply incorrect. Consider the sentences below: (62) We refused to let our baby stay up all night, so he threw the book at us. He yelled and screamed for hours.</Paragraph>
    <Paragraph position="2"> (63) My pals asked me how I got straight A's. I managed to explain it away by telling them it was a bureaucratic mistake.</Paragraph>
    <Paragraph position="3"> In each one of these sentences, a lexical presupposition is being violated. Our baby, as we all know, is not really an authority, as required of the actor of the phrase throw the book. Therefore, Sentence (62) sounds ironic. A presuppositional condition is violated also in sentence (63). The entire presupposition states: (a) a planning failure by the actor, (b) a threatening act by a social authority, and (c) an explanation act taken to block that punishment. Now, getting A's is not a planning failure, rather it is a fortuitous success, which makes the situation humorous. Consider the next pair of sentences: null (64) I made an appointment with my advisor. I met him on time.</Paragraph>
    <Paragraph position="4"> (65) I made an appointment with my advisor. I ran into him on time.</Paragraph>
    <Paragraph position="5"> Both run into and meet make the same statement: two characters got into a physical proximity. However, since run into presupposes an unplanned, surprising element which does not exist in the situation, sentence (65) sounds incorrect. In contrast to previous research in which presupposition was used for deriving secondary inferences which are mostly redundant, we suggest using presuppositions for disambiguation, detection of Computational Linguistics, Volume 13, Numbers 3-4, July-December 1987 325 Uri Zernik and Michael G. Dyer The Self-Extending Phrasal Lexicon irony \[Dyer86a\], and even for generation of irony by a computer (by applying phrases in situations where a presuppositional condition has been slightly mutated).</Paragraph>
  </Section>
class="xml-element"></Paper>