A Psycholinguistically Motivated Parser for CCG
| Autor: | Michael Niv |
|---|---|
| Rok vydání: | 1994 |
| Předmět: |
FOS: Computer and information sciences
Parsing Computer Science - Computation and Language Categorial grammar Grammar business.industry Computer science media_common.quotation_subject Syntactic ambiguity Emergent grammar Combinatory categorial grammar Mildly context-sensitive grammar formalism computer.software_genre Syntax TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES Artificial intelligence business computer Computation and Language (cs.CL) Natural language processing media_common |
| Zdroj: | ACL |
| DOI: | 10.48550/arxiv.cmp-lg/9406031 |
| Popis: | Considering the speed in which humans resolve syntactic ambiguity, and the overwhelming evidence that syntactic ambiguity is resolved through selection of the analysis whose interpretation is the most `sensible', one comes to the conclusion that interpretation, hence parsing take place incrementally, just about every word. Considerations of parsimony in the theory of the syntactic processor lead one to explore the simplest of parsers: one which represents only analyses as defined by the grammar and no other information. Toward this aim of a simple, incremental parser I explore the proposal that the competence grammar is a Combinatory Categorial Grammar (CCG). I address the problem of the proliferating analyses that stem from CCG's associativity of derivation. My solution involves maintaining only the maximally incremental analysis and, when necessary, computing the maximally right-branching analysis. I use results from the study of rewrite systems to show that this computation is efficient. Comment: 8 pages, LaTeX, requires psfig.tex, 2 figures in separate file |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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