By António Branco, Tony McEnery, Ruslan Mitkov
Anaphora processing is a primary subject within the learn of common language and has lengthy been the thing of analysis in quite a lot of disciplines. the proper interpretation of anaphora has additionally turn into more and more very important for real-world common language processing purposes, together with desktop translation, automated abstracting, info extraction and query answering.
This quantity presents a special assessment of the processing of anaphora from a multi- and inter-disciplinary perspective. will probably be of curiosity and functional use to readers from fields as different as theoretical linguistics, corpus linguistics, computational linguistics, desktop technological know-how, typical language processing, man made intelligence, human language expertise, psycholinguistics, cognitive technological know-how and translation studies.
The readership comprises yet isn't really constrained to school academics, researchers, postgraduate and senior undergraduate students.
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Additional info for Anaphora Processing: Linguistic, Cognitive and Computational Modelling
The following sections will analyse, within the ARengine framework, a set of AR cases, usually considered difficult to interpret. The discussion intends to evidence specific difficulties inherent to a large range of anaphoric phenomena, to imagine solutions in terms of an AR model, by indicating knowledge sources and rules/heuristics capable to deal with the identified tasks and to informally appreciate the tractability of these solutions. The discussion remains under the universal panacea for all the failures in AR, world knowledge (WK).
We will suppose a knowledge source capable to apply syntactic criteria in order to fetch a apposition-of=RE1 slot attached to PS2. As PS1 should have matched a DE1 the moment PS2 is being processed, a certifying rule must unify PS2 with DE1, in case RE2 is a definite determined NP, undetermined NP or a genitival construction. As a result, DE1 will accumulate all the attributes of PS2. Examples of cases correctly interpreted following this strategy are:10 (Emmanuel Goldstein), (the Enemy of the People); (the primal traitor), (the earliest defiler of the Party's purity).
If RE1 is nested on RE2 on the text layer, a knowledge source should fetch the value RE1 to a nesting slot of the PS corresponding to RE2. On DE2 of the semantic layer, this slot will later on be transformed, by an attribute-filling rule, into a belongs-to (or some variation of it) attribute indicating the DE corresponding to RE1. Other constructions where a belongs-to or variations of it are correctly included are:9 (the center of (the hall opposite the big telescreen)), (emblem of (the Junior Anti-Sex League)), (one of (the middle rows)), (one of (them)), (one of (the novel-writing machines)).