A shallow processing approach to anaphor resolution
The thesis describes an investigation of the feasibility of resolving anaphors in natural language texts by means of a ~shallow processing~ approach which exploits knowledge of syntax, semantics and local focussing as heavily as possible; it does not rely on the presence of large amounts of world or domain knowledge, which are notoriously hard to process accurately. The ideas reported are implemented in a program called SPAR (Shallow Processing Anaphor Resolver), which resolves anaphoric and other linguistic ambiguities in simple English stories and generates sentence-by-sentence paraphrases that show what interpretations have been selected. Input to SPAR takes the form of semantic structures for single sentences constructed by Boguraev's English analyser. These structures are integrated into a network-style text representation as processing proceeds. To achieve anaphor resolution, SPAR combines and develops several existing techniques, most notably Sidner's theory of local focussing and Wilks' ~preference semantics~ theory of semantics and common sense inference. Consideration of the need to resolve several anaphors in the same sentence results in Sidner's framework being modified and extended to allow focus-based
Carter, David Maclean
anaphors ; natural language ; shallow processing ; local focussing ; preference semantics ; common sense inference ; sentence analysis ; Information technology ; Computational linguistics
A shallow processing approach to anaphor resolution. The thesis describes an investigation of the feasibility of resolving anaphors in natural language texts by means of a ~shallow processing~ approach which exploits knowledge of syntax, semantics and local focussing as heavily as possible; it does not rely on the presence of large amounts of world or domain knowledge, which are notoriously hard to process accurately. The ideas reported are implemented in a program called SPAR (Shallow Processing Anaphor Resolver), which resolves anaphoric and other linguistic ambiguities in simple English stories and generates sentence-by-sentence paraphrases that show what interpretations have been selected. Input to SPAR takes the form of semantic structures for single sentences constructed by Boguraev's English analyser. These structures are integrated into a network-style text representation as processing proceeds. To achieve anaphor resolution, SPAR combines and develops several existing techniques, most notably Sidner's theory of local focussing and Wilks' ~preference semantics~ theory of semantics and common sense inference. Consideration of the need to resolve several anaphors in the same sentence results in Sidner's framework being modified and extended to allow focus-based
shallow processing anaphor resolution describe investigation feasibility resolve anaphor natural_language text mean shallow processing exploit knowledge syntax_semantics local focus heavily possible rely presence_large amount world domain knowledge notoriously hard process accurately idea report implemented program call shallow processing anaphor resolve anaphoric linguistic ambiguity simple english story generate sentence sentence paraphrase show interpretation select input take_form semantic_structure single sentence construct english analyser structure integrate network style text representation processing proceeds achieve anaphor resolution combine develop several exist technique notably theory local focus preference semantics theory semantics common_sense inference consideration need resolve several anaphor sentence framework modify extended allow focus based