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<Paper uid="W05-1527">
  <Title>SUPPLE: A Practical Parser for Natural Language Engineering Applications</Title>
  <Section position="4" start_page="1" end_page="200" type="metho">
    <SectionTitle>
2 The SUPPLE Parser
</SectionTitle>
    <Paragraph position="0"> SUPPLE is a general purpose bottom-up chart parser for feature-based context free phrase structure gram- null In previous published materials and in the current GATE release the parser is referred to as buChart. This is name is now deprecated.</Paragraph>
    <Paragraph position="1"> mars (CF-PSGs), written in Prolog, that has a number of characteristics making it well-suited for use in LE applications. It is available both as a language processing resource within the GATE General Architecture for Text Engineering (Cunningham et al., 2002) and as a standalone program requiring various preprocessing steps to be applied to the input. We will here list some of its key characteristics.</Paragraph>
    <Paragraph position="2"> Firstly, the parser allows multiword units identified by earlier processing components, e.g. named entity recognisers (NERs), gazetteers, etc, to be treated as non-decomposable units for syntactic processing. This is important as the identification of such items is an essential part of analyzing real text in many domains.</Paragraph>
    <Paragraph position="3"> The parser allows a layered parsing process, with a number of separate grammars being applied in series, one on top of the other, with a &amp;quot;best parse&amp;quot; selection process between stages so that only a sub-set of the constituents constructed at each stage is passed forward to the next. While this may make the parsing process incomplete with respect to the total set of analyses licensed by the grammar rules, it makes the parsing process much more efficient and allows a modular development of sub-grammars.</Paragraph>
    <Paragraph position="4"> Facilities are provided to simplify handling feature-based grammars. The grammar representation uses flat, i.e. non-embedded, feature representations which are combined used Prolog term unification for efficiency. Features are predefined and source grammars compiled into a full form representation, allowing grammar writers to include only relevant features in any rule, and to ignore feature ordering. The formalism also permits disjunctive and optional right-hand-side constituents.</Paragraph>
    <Paragraph position="5"> The chart parsing algorithm is simple but very  efficient, exploiting the characteristics of Prolog to avoid the need for active edges or an agenda. In informal testing, this approach was roughly ten times faster than a related Prolog implementation of standard bottom-up active chart parsing.</Paragraph>
    <Paragraph position="6"> The parser does not fail if full sentential parses cannot be found, but instead outputs partial analyses as syntactic and semantic fragments for userselectable syntactic categories. This makes the parser robust in applications which deal with large volumes of real text.</Paragraph>
  </Section>
  <Section position="5" start_page="200" end_page="200" type="metho">
    <SectionTitle>
3 The Sample Grammar
</SectionTitle>
    <Paragraph position="0"> The sample grammar distributed with SUPPLE has been developed over several years, across a number LE projects. We here list some key characteristics.</Paragraph>
    <Paragraph position="1"> The morpho-syntactic and semantic information required for individual lexical items is minimal -inflectional root and word class only, where the word class inventory is basically the PTB tagset.</Paragraph>
    <Paragraph position="2"> A conservative philosophy is adopted regarding identification of verbal arguments and attachment of nominal and verbal post-modifiers, such as prepositional phrases and relative clauses. Rather than producing all possible analyses or using probabilities to generate the most likely analysis, the preference is to offer a single analysis that spans the input sentence only if it can be relied on to be correct, so that in many cases only partial analyses are produced. The philosophy is that it is more useful to produce partial analyses that are correct than full analyses which may well be wrong or highly disjunctive. Output from the parser can be passed to further processing components which may bring additional information to bear in resolving attachments.</Paragraph>
    <Paragraph position="3"> An analysis of verb phrases is adopted in which a core verb cluster consisting of verbal head plus auxiliaries and adverbials is identified before any attempt to attach any post-verbal arguments. This contrasts with analyses where complements are attached to the verbal head at a lower level than auxiliaries and adverbials, e.g. as in the Penn TreeBank. This decision is again motivated by practical concerns: it is relatively easy to recognise verbal clusters, much harder to correctly attach complements.</Paragraph>
    <Paragraph position="4"> A semantic analysis, or simplified quasi-logical form (SQLF), is produced for each phrasal constituent, in which tensed verbs are interpreted as referring to unique events, and noun phrases as referring to unique objects. Where relations between syntactic constituents are identified in parsing, semantic relations between associated objects and events are asserted in the SQLF.</Paragraph>
    <Paragraph position="5"> While linguistically richer grammatical theories could be implemented in the grammar formalism of SUPPLE, the emphasis in our work has been on building robust wide-coverage tools -- hence the requirement for only minimal lexical morphosyntactic and semantic information. As a consequence the combination of parser and grammars developed to date results in a tool that, although capable of returning full sentence analyses, more commonly returns results that include chunks of analysis with some, but not all, attachment relations determined.</Paragraph>
  </Section>
  <Section position="6" start_page="200" end_page="200" type="metho">
    <SectionTitle>
4 Downloading SUPPLE Resources
</SectionTitle>
    <Paragraph position="0"> SUPPLE resources, including source code and the sample grammar, and also a longer paper providing a more detailed account of both the parser and grammar, are available from the supple homepage at: http://nlp.shef.ac.uk/research/supple</Paragraph>
  </Section>
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