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<?xml version="1.0" standalone="yes"?> <Paper uid="P81-1016"> <Title>I~IGATION OF PROCESSING STRATEGIES FOR THE STRUCTURAL ANALYSIS OF ARGOMF/Trs</Title> <Section position="1" start_page="0" end_page="0" type="metho"> <SectionTitle> I~IGATION OF PROCESSING STRATEGIES FOR THE STRUCTURAL ANALYSIS OF ARGOMF/Trs </SectionTitle> <Paragraph position="0"/> </Section> <Section position="2" start_page="0" end_page="0" type="metho"> <SectionTitle> 2. THE UNDERSTANDING PROCESS </SectionTitle> <Paragraph position="0"> This paper outlines research on processing strategies being developed for a language understanding systerN, designed to interpret the structure of arguments. For the system, arguments are viewed as trees, with claims as fathers to their evidence. Then understanding becomes a problem of developing a representative argtmlent tree, by locating each proposition of the argument at its appropriate place. The processing strategies we develop for the hearer are based on expectations that the speaker will use particular coherent transmission strategies and are designed to be fairly efficient (work in linear time). We also comment on the use by the speaker of linguistic clues to indicate structure, illustrating how the hearer can interpret the clues to limit his processing search and thus improve the co~lexity of the understanding process.</Paragraph> <Section position="1" start_page="0" end_page="0" type="sub_section"> <SectionTitle> 2.1 PROCI.~ING S'I~AT~GIES </SectionTitle> <Paragraph position="0"> To prOcess an argument, each proposition is analyzed in turn. It is convenient to think of the representation for an argument as a tree with claims as fathers to their evidence. The speaker thus has a particular tree structure for the argument which he tranm~its in some order. The hearer must take the incoming stream of propositions and re-construct the logical structure tree. Although the speaker has available a wide variety of possible transmission algorithms, we claim that only a small n,~ber of these will be used. We look for tranm~ission algorithms that have associated reception algorithms such that both S and H can process in a reasonable amount of time. Consider the following strategies= i. BACKC4~DUND This paper focuses on one aspect of an argument understanding system currently being designed. An overview of the initial design for the system can be found in \[Cohen 88\]. In general, we are examining one-sided arguments, where the speaker (S) tries to convince the hearer (H) of a particular point of view. We then concentrate on the analysis problem of determining the overall structure of the argtm~nt.</Paragraph> <Paragraph position="1"> Considering an argument as a series of propositions, the structure is indicated by isolating those propositions which serve as CLAIMS and those which serve as EVIDENCE for a particular claim, and by indicating how each piece of evidence sup~orta its associated claim. A proposition E is established as evidence for a proposition C if they fit appropriate slots in one of the system frames representing various logical rules of inference, such that E is a premise to C's conclusion. For example, E will be evidence for C according to modus ponens if E-->C is true..</Paragraph> <Paragraph position="2"> Establishing evidence is a complex process, involving filling in missing premises and recognizing the logical connection between propositions. In any case, our research does focus on reconstructing this logical form of the argument, aside from judgments of credibility.</Paragraph> <Paragraph position="3"> The initial design \[Cohen 8g\] adopts an unsophisticated processing strategy: each proposition is analyzed, in turn, and each is tested out as possible evidence for every other proposition in the argument. The current design seeks to imprOve that basic strate< ! to a selective process where the analysis for a given proposition is performed with respect to the interpretation for the overall argument so far. So, only particular propositions are judged eligible to affect the interpretation of the proposition currently being analyzed. Currently, we assume an &quot;evidence oracle&quot; which, given two propositions, will decide (yes or no) whether one is evidence for the other. With this &quot;accepted&quot; authority, a representation for the argument can be built as the analysis proceeds. (The design of the oracle is another research area altogether, not discussed in this paper).</Paragraph> <Paragraph position="4"> a) 9RE-ORDER The most straightforward transmission for an argL~nent is to present a claim, followed by its evidence, where any particular piece of evidence may, in turn, have evidence for it, following it. A sample tree (numbers indicate order of propositions in the transmitted stream) is:</Paragraph> </Section> </Section> <Section position="3" start_page="0" end_page="72" type="metho"> <SectionTitle> 4 6/5~/ </SectionTitle> <Paragraph position="0"> In this kind of argtmlent, every claim precedes its evidence. Thus, w~en the hearer tries to find an interpretation for a current proposition, he must only search prior propositions for a father. The reception algorithm we propose for H is as follows: to interpret the current proposition, NE~, consider the proposition immediately prior to it (call it L for last). I) Try out NEW as evidence for L . 2) If that fails, try NER as evidence for each of L's ancestors, in turn, up to the root of the tree. (NEW's father must exist somewhere on this &quot;right border&quot; of the tree). When the location for NEW is found, a node for it is added to the tree, at the appropriate place.</Paragraph> <Paragraph position="1"> b) 9OST-ORDKR Here, each claim is preceded by its evidence. This is a little more complex for the hearer because he may accept a whole stream of propositions without knowing how they relate to each other until the father for all of them is found. Exa~le: . 9,-~ The reception for H must now make use of the tree for the argument built so far and must keep track of propositions whose interpretation is not yet known, 9ending the appearance of their father. The formal reception algorithm will thus make use of a stack.</Paragraph> <Paragraph position="2"> Consider L to be the top of the stack. To interpret the current proposition NEW do the following- I) See if NEW ~ets evidence from L (i.e. is claim for L). 2al If L is evidence, keep popping off elements of the stack that are also sons and push the resulting tree onto the stack. 2b) Otherwise, push ~ onto the stack. In short, search for sons: when one son is found, all of them can be picked up. Then the father must stack up to De evidence for same future proposition.</Paragraph> <Paragraph position="3"> c) HYBRID Pre-order and post-order are two consistent strategies which the hearer can recognize if he expects the argument to conform to one or the other transmission rules, throughout. But an argument essentially consists of a series of sub-arguments (i.e. a claim plus its evidence). And the Speaker may thus decide to transmit some of these sum-arguments in pre-order, and others in post-order, yielding an overall h~rid argument. Therefore, the hearer must develop a more general processing strategy, to recognize hybrid transmission. The reception algorithm now is a c~mDination of techniques from a) and b).</Paragraph> <Paragraph position="4"> Exam-ple: ,~...</Paragraph> <Paragraph position="5"> 23 ,6~ (EX 3) But there are additional complications to processing in this model - for example, transitive evidence relations. In KX 3, 4 and 5 are evidence for 1 (since 4 and 5 are evidence for 6 and 6 is evidence for i), so they will De attached to I initially. Then, to process 6, H must attach it to i and pick up 4 and 5 as sons. So, the hybrid algorithm involves recovering descendants that may alreaay De linked in the tree. Here is a more detailed description of the algorithm: We maintain a dummy node at the top of the tree, for which all nodes are evidence. Consider L to De a pointer into the tree, representing the lowest possible node that can receive more evidence (initially set to dummy). For every node NEN on the input stream do the following: forever do (B0:) if NEW evidence for L then (Sl:) if no sons of L are evidence for NEW then /* just test lastson for evidence */ (BII:) attach NEW below L (Bl2:) set L to NEW exit forever loop (B2:) else (B21:) attach all sons of L which are evidence for NEW below NE~ /* attach lastson; bump ptr. to lastson */ /* back I and keep testing for evidence */ (B22:) attach NE~ below L exit forever loop (B3:) else set L to father(L) end forever loop This hyt)rid model still accounts for only sc~e of many possible argtm~ent configurations. But we claim that it is a good first approximation to a realistic and efficient processing strategy for arguments is general. It captures the argument structure a hearer may expect from a speaker. Some of the restrictions of this model include: (i) importance of the last proposition before NEW in the analysis of NEW; (2) preference for relations with propositions closer to NEW; (3) considering only the last brother in a set of evidence when NEW seeks to relate to prior propositions. Note then that we do not expect to add evidence for a brother or uncle of L - these nodes are closed off, as only the last brother of any particular level is open for further expansion. To determine the appropriateness of this algorithm as a general strategy, we are currently investigating the i~l ications of restricting expected argtnnent structures to this class and the complexity in co~.re/~ension caused Dy other transmission me,hods. Now, the reception algorithms we develop for a), b), and c) can all be shown to ~ork in linear time (the n~r of evidence relations to be ~ested will be proportional to the numDer of nodes in the tree) \[see Appendix\] but not in real time (can have aDritrarily long c~ains in any suD-argtmlent). Yet hearers process argt~nents well and this, we claim, is because the speaker helps out, providing special clues to the structure.</Paragraph> <Section position="1" start_page="71" end_page="72" type="sub_section"> <SectionTitle> 2.2 LINGUISTIC CLUES </SectionTitle> <Paragraph position="0"> Special words and phrases are often used Dy the speaker to suggest the structure of the argument. One main use of clues is to re-direct the hearer to a particular proposition. Phrases like &quot;Let us now return to...&quot; followed Dy a specific indication of a prior topic are often used in this respect. In EX l, if 8 is preceded Dy a clus suggesting its link to i, then the hearer is spared the long chain of trying 8 as evidence for 7, 5 and 3. So, linear time algorithms can become real time with the aid of clues.</Paragraph> <Paragraph position="1"> But clues of re-direction may also occur to maintain poorly structured arguments - i.e. the speaker can re-direct the hearer to parts of the argument that were &quot;closed off&quot; in his processing. In certain cases, expectations are then set up to address intermediary propositions. We are developing a detailed theory of how to process subsequent to re-direction.</Paragraph> <Paragraph position="2"> Another use of clues is to indicate boundaries. In EX 3, if a phrase like &quot;We now consider another set of evidence for (i)...= preceded 4, it would be easier for H to retrieve 4 and 5 as sons to 6 (without checking 3 as well).</Paragraph> <Paragraph position="3"> Explicit ~rases a~out relations between propositions are only one type of clue. There are, in ~ition, Special words and phrases with a function of connectir~ a proposition to some preceding statement.</Paragraph> <Paragraph position="4"> These clues aid in the processing of an arg~uent by restricting the possible interpretation of the proposition containing the clue, and hence facilitating the analysis for that proposition. As outlined in section 2.1, the analysis of a proposition involves a constrained search through the list of prior propositions. With these clues, the search is (i) guaranteed to find ~ prior proposition wtlic~ relates to the one with the clue (2) restricted even further due to the semantics of the clue as to the desired relation between the prior and current proposition (e.g. MUSt be son, etc.). We develop a taxonomy of connectives ~ised on the &quot;logical connectors&quot; listed in (Quirk 721, and assign an interpretation rule to each class.</Paragraph> <Paragraph position="5"> Notation: in the following discussion S represents the proposition with the connective clue, and P represents the prior proposition ~nich &quot;connects&quot; to $.</Paragraph> </Section> </Section> <Section position="4" start_page="72" end_page="73" type="metho"> <SectionTitle> Smeary: CATSGORY RELATICN:P to S EXAMPLE </SectionTitle> <Paragraph position="0"> parallel brother &quot;Secondly&quot; inference son &quot;As a result&quot; detail father &quot;In particular&quot; summary multiple sons &quot;In conclusion&quot; reformulation son A~D father &quot;In other words&quot; contrast Son OR brother &quot;on the other hand&quot; Remark: The examples in the following discussion are intended to illustrate the processing issues in argument analysis. We are examining several real life examples from various sources (e.g. rhetoric books, letters to the editor, etc.) but these introduce issues in the operation of the evidence oracle, and so are not shown here.</Paragraph> <Paragraph position="1"> i) Parallel: This category includes the most basic connectors like &quot;in addition&quot; as well as lists of clues (e.g. &quot;First, Secondly, Thirdly,..etc.&quot;). P must be a brother to S. Since we only have an oracle which tests if A is SON of B, finding a brother must involve locating the crayon father first.</Paragraph> <Paragraph position="2"> EX 4: l)The city is in serious trouble rl\ 2)There are sc~e dangerous fires going 2 4 3)Three separate blazes have broken out ~ 3 4)In addition, a tornado is passing through The parallel category has additional rules for analysis in cases where lists of clues are present.</Paragraph> <Paragraph position="3"> Then, all propositions with clues from the same list must relate. But we note that it is not always a brother relation between these specific propositions. The relation is, in fact, that the brothers are the propositions which serve as claims in each sub-argtm~ent controlled by a list clue.</Paragraph> <Paragraph position="4"> EX 5: l)The city is awful 1 2)First, no one cleans the parks ~\ 3)So the parks are ugly 3 4 4)Then, the roads are ugly, too / \ 5)There's always garbage there 2 5 Here, 2 and 4 contain the clues, but 3 and 4 are brothers.</Paragraph> <Paragraph position="5"> Here, 3 finds 2 as its father.</Paragraph> <Paragraph position="6"> 4)Summary: We note that some phrases of summary are used in a reformulation sense and would be analyzed according to that category's rules. These are cases where the summarizing is essentially a repeat of a proposition stated earlier. A &quot;summary&quot; suggests that a set of sons are to be found.</Paragraph> <Paragraph position="7"> The interpretation rule for summary would follow the general reception algorithm to pick up all sons at the same level.</Paragraph> <Paragraph position="8"> 5)Reformulation: When a clue indicates that S is essentially &quot;equivalent&quot; to some P, P must satisfy the test for both son and father. To represent t/~is relation, we may need an extension to our current tree model (see Section 3 - Future Work).</Paragraph> <Paragraph position="9"> EX 10: l)We need money 2)In other words, we are broke 6)Contrast: This category covers a lot of special phrases with different uses in arguments, we have yet to decide how to optimally record contrastive propositions. For now, we'd say that a proposition which offers contrast to some evidence for a claim is (counter) evidence for that claim, and hence S is son of P. And a proposition which contrasts another directly, without evidence being presented is a (counter) claim, and hence S is a brother to 9.</Paragraph> <Paragraph position="10"> EX II: l)The city's a disaster 1 2)The parks are full of uprooted trees \~ 3)But at least the playgrounds are safe 2 3 Here, 3 is counter evidence for 1 EX 12: 1)The city is dangerous ~5~ 2)The parks have muggings 3)But the city is free of pollution 4 3 1 4)And there are great roads / 5)So, I think the city's great 2 Here 3 and 1 are brothers There are a lot of issues surrounding contrast, some of which we mention briefly here to illustrate. One question is how to determine which proposition is &quot;counter&quot; to the rest of the argument. In EX 12, the proposition with the clue was not the contrastive statement of the argument. So, it is not straightforward to expand our simplified recording of contrast statements to add a &quot;counter&quot; label. Another feature is the expectations set for the future when contrast appears. Sometimes, more evidence is expected, to weigh the argument in favour of one position over another. If these expectations are characterized, future processing may be facilitated. This description of connective clues is intended to illustrate some of the aids available to the hearer to restrict the interpretation of propositions, we are still working on complete descriptions for the interpretation rules. In addition, we intend each class to be distinct, but we are aware that some English phrases have more than one meaning and may thus be used in more than one of the taxonomy's categories. For these cases, the union of possible restrictions may have to be considered.</Paragraph> <Section position="1" start_page="72" end_page="73" type="sub_section"> <SectionTitle> 2.3 IMPLICATIONS OF THIS ANALYSIS DESIC~ </SectionTitle> <Paragraph position="0"> Our description of various processing strategies and clue interpretations can be construed as a particular theory of how to process arguments. The hearer expects the speaker to conform to certain tranmnission strategies - i.e. does not expect a random stream of propositions. But, H may be confronted with re-directions in the form of special clues, which he interprets as he finds. And he may limit his searching and testing by interpreting clues suggesting either the kind of relation to search for (evidence for, claim for) or the specific propositions to check. The theory thus proposes a particular selective interpretation process, the techniques are given a formal treatment to illustrate their complexity, and the special markers confronted in analysis are assigned a functional interpretation - to improve the ccm~)lexity of the understanding task. A note here on the &quot;psychological validity&quot; of our model: we have tried to develop processing strategies for arguments that are consistent with our intuitions on how a hearer would analyze and that function with a realistic complexity. But, we make no claims that this is the way all humans would process.</Paragraph> </Section> </Section> <Section position="5" start_page="73" end_page="73" type="metho"> <SectionTitle> 3. ~ CONSIDERATIONS </SectionTitle> <Paragraph position="0"> One area we have not discussed in this paper is that of establishing the evidence relation. For now, the problem is isolated into the &quot;evidence oracle = which performs the necessary semantic processing. In the future, we will give more details on the complexities of this module and its interaction with the general processing strategy described here.</Paragraph> <Paragraph position="1"> There are, as well, several i~provements in processing techniques to consider. Here are some ongoing projects - i) Investigation of other possible argument structures . not included here. The most obvious case to consider is: a claim, both preceded and followed by evidence for it. This is a reasonable tran.maission to expect. We are working on extensions to the hybrid algorit~ to accept these configurations as well. One interesting issue is the necessity for linguistic clues with argument structures of this type - to make sure the hearer can pick up additional evidence and recognize where the next suJo-argument begins.</Paragraph> <Paragraph position="2"> 2) Expanding the existing representation model to handle other complications in arguments. In particular, there a~e several different types of multiple roles for a proposition, which ~Jst all be handled by the theory. These include: (i) Proposition is both claim and evidence. (This is already arx:x:uKxlated in our current tree design, where a node can have father and sons). (ii) Proposition is both claim and evidence for the same proposition i.e. two &quot;equivalent&quot; propositions in the argument. (iii) Proposition is claim to several other propositions. (Again, currently acceptable as father can have any number of sons). (iv) Proposition (E) is evidence for more than one proposition. If all the claims form an ancestral chain - father, grandfather, great-grandfather, etc. then this is just the transitive evidence relation discussed previously and handled by the current strategy. In other cases, (for example, when the -..laims are brothers) the hearer may not recognize the multiple cole in all possible tranmuissions. For instance, a tranmuission of claiml, E, then claim/ seeus comprehensible. But if the hearer received them in the order: claiml, claim/, then E - would he recover the role of E as evidence for claiml? 3) Trying to characterize the ~,~lexity of various argument configurations. Certain combinations of pre and poet order seem less taxing to the hearer. We are examining the cases where complexity problems arise and linguistic clues become more prevalent.</Paragraph> </Section> <Section position="6" start_page="73" end_page="74" type="metho"> <SectionTitle> 4. NELATED WORK </SectionTitle> <Paragraph position="0"> Alt~.,ugh our research area may be considered largely unexplored (examining a specific kind of conversation (the argument), concentrating on structure, and developing formal descriptions of processing), there are some relevant references to other work. In \[Ho~os 8%\] Hotels states that &quot;T~e proOl~m of AI is how to control inferencing and oti~er search processes, so that the best answer will be found within the resource limitations.&quot; We share this oommittment to designing natural language understanding systams w~ich perform a selective analysis of the input. The actual restrictions on processing differ in various existing syste~ according to the language tasks and the underlying representation scheme.</Paragraph> <Paragraph position="1"> In \[Grosz 77\] focus spaces are used to search for referents to definite noun ~rases (and to solve other linguistic problems). These spaces of objects are arranged to form a hierarchy with an associated visibility lattice, based on the underlying structure of the task of the dialogue. O~r tree representation is also a-'~erarchical structure and the description of propositions eligible to relate to the current one may be viewed as a visibility requirement on that hierarchy. So, the restrictions to processing in both our systems can be described similarly, although the details of the design differ to accommodate our different research areas.</Paragraph> <Paragraph position="2"> In So.bank's work on story understar~ing (e.g.</Paragraph> <Paragraph position="3"> \[Schank 75\]) snerentyped scripts are used to limit processing. Here, a given proposition is analyzed by tryir~ to fit with expectations for content generated by slota of the script not yet filled. With arguments, we cannot predict future content, so we design expectations that future propositions will have a particular structure with respect to the text so far. These are in fact expectations for coi~erent transmission. Schan~'s expectations for coherence, on the other hand, are coincident with his expectations for content, driven by scripts.</Paragraph> <Paragraph position="4"> Our actual design for restricting analysis is similar in many respects to Hotels' work on coherence relations ( \[HobbS 76\], \[Ho~s78\]). In this work, the representation for the text is also a tree, but the connections between nodes are coherence relations subordinating relations between father and son, and co-ordinating relations between brothers. In C~?~,,on to both designs is the proposal to construct restricted lists of propositions eligible to relate to a current proposition. In our case, the relations between nodes in the tree is quite different (claim, evidence), although the description for the restricted set turns out to be the same - nawely, the right border of the tree.</Paragraph> <Paragraph position="5"> In ~__~Npbs_ ' system, the search for an interpretation is narrowed by proceseing a &quot;goal list&quot; of desired relations to existing propositions. We do not have a goal list to order our search, but merely a list of eligible propositions and an ordering of these 5ased on proxi~ty to the current proposition. But we also furnish some motivation for the construction of the eligible list - naDely, from the bearer's expectations about transmiseion strategies used by the speaker.</Paragraph> <Paragraph position="6"> In addition, Ho~ mentions that a few special words initiate specific goals (for example, &quot;and&quot; suggests temporal succession, parallel or possibly contrast).</Paragraph> <Paragraph position="7"> In our system we also discuss the restrictions to processing furnished by clues but i) we define the corpus of clues more clearly, indicating several types and their associated restrictions and 2) we make clear the relation between restrictions from clues and the general processing strategy - that analysis picks up clues first, and resorts to general techniques otherwise. Furthermore, we show that a) most classes of clues are simply a restriction on the list of eligible propositions proposed for a general processing strategy and b)certain types of clues may override the general restrictions of the eligible list (e.g. re-directing the hearer explicitly).</Paragraph> <Paragraph position="8"> I am gz ~teful to Ray Perrault and their suggestions for this paper.</Paragraph> </Section> class="xml-element"></Paper>