Anaphora Resolution: Theory and Practice

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Hypotheses Derived from Previous Work• pronoun resolution in written text works reasonably well without consideringknowledge- or semantics-based features;• for determining non-NP-antecedents of pronouns domain knowledge seemsto be necessary (Byron, 2002);• Eckert & Strube (2000) had the hypothesis that information aboutsubcategorization frames of verbs gathered from corpora (e.g. Briscoe &Caroll (1997)) could be sufficient.
Data: Corpus• 20 randomly chosen Switchboard dialogues;• 30810 tokens (words, punctuation) in 3275 sentences/1771 turns;• annotation consists of 16601 NP- and non-NP-markables;• identification of markables and assignment of attributes guided by PennTreebank;• 924 third person neuter pronouns: 43.4% have NP-antecedents, 23.6% non-NP-antecedents, 33% have no antecedents (almost identical to the numbersreported by Eckert & Strube, 2000).
Page 1 and 2: Anaphora Resolution:Theory and Prac
Page 3 and 4: Anaphora Resolution:orTheory and Pr
Page 5 and 6: A Few Questions• How do insights
Page 7 and 8: Never Look Back: An Alternative to
Page 9 and 10: NLB: The Algorithm1. If a referring
Page 11 and 12: NLB: Results• results obtained by
Page 13 and 14: Application: Anaphora Resolution in
Page 15 and 16: Anaphora Resolution in Spoken Dialo
Page 17 and 18: Types of Anaphora II: Discourse-Dei
Page 19 and 20: Types of Anaphora IV: Inferrable-Ev
Page 21 and 22: Proposal for Pronoun Resolution in
Page 23 and 24: I-Incompatible (*I)x is an anaphor
Page 25 and 26: The Algorithm: Switchboard sw311728
Page 27 and 28: Problems with These Approaches• o
Page 29 and 30: Application: Anaphora Resolution in
Page 31 and 32: NP-level FeaturesDocument level fea
Page 33 and 34: Different Results for Different Typ
Page 35 and 36: Low Amount of Training Data for Pro
Page 37: Application: Pronoun Resolution for
Page 41 and 42: Data: Distribution of Agreement Fea
Page 43 and 44: Features• NP-level features;• c
Page 45 and 46: Coreference-level Features11. agree
Page 47 and 48: Experimental SetupAnnotated CorpusC
Page 49 and 50: Iterative Procedure(similar to wrap
Page 51 and 52: Results: 3ncorrect found total foun
Page 53 and 54: Results: Combinedcorrect found tota
Page 55 and 56: Conclusions: ML for Pronoun Resolut
Page 57 and 58: Conclusions IIHowever,• I used di
Page 59: Further Information (Papers, Annota

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