Resolving It, This, and That in Unrestricted Multi-Party Dialog

Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pages 816–823, Prague, Czech Republic, June 2007. c⃝2007 Association for Computational Linguistics Resolving It, This, and That in Unrestricted Multi-Party Dialog Christoph M¨uller EML Research gGmbH Villa Bosch Schloß-Wolfsbrunnenweg 33 69118 Heidelberg, Germany christoph.mueller@eml-research.de Abstract We present an implemented system for the resolution of it, this, and that in tran- scribed multi-party dialog. The system han- dles NP-anaphoric as well as discourse- deictic anaphors, i.e. pronouns with VP an- tecedents. Selectional preferences for NP or VP antecedents are determined on the basis of corpus counts. Our results show that the system performs significantly better than a recency-based baseline. 1 Introduction This paper describes a fully automatic system for resolving the pronouns it, this, and that in unre- stricted multi-party dialog. The system processes manual transcriptions from the ICSI Meeting Cor- pus (Janin et al., 2003). The following is a short fragment from one of these transcripts. The letters FN in the speaker tag mean that the speaker is a fe- male non-native speaker of English. The brackets and subscript numbers are not part of the original transcript. FN083: Maybe you can also read through the - all the text which is on the web pages cuz I’d like to change the text a bit cuz sometimes [it]1’s too long, sometimes [it]2’s too short, inbreath maybe the English is not that good, so in- breath um, but anyways - So I tried to do [this]3 today and if you could do [it]4 afterwards [it]5 would be really nice cuz I’m quite sure that I can’t find every, like, ortho- graphic mistake in [it]6 or something. (Bns003) For each of the six 3rd-person pronouns in the exam- ple, the task is to automatically identify its referent, i.e. the entity (if any) to which the speaker makes reference. Once a referent has been identified, the pronoun is resolved by linking it to one of its an- tecedents, i.e. one of the referent’s earlier mentions. For humans, identification of a pronoun’s referent is often easy: it1, it2, and it6 are probably used to refer to the text on the web pages, while it4 is prob- ably used to refer to reading this text. Humans also have no problem determining that it5 is not a normal pronoun at all. In other cases, resolving a pronoun is difficult even for humans: this3 could be used to refer to either reading or changing the text on the web pages. The pronoun is ambiguous because evi- dence for more than one interpretation can be found. Ambiguous pronouns are common in spoken dialog (Poesio & Artstein, 2005), a fact that has to be taken into account when building a spoken dialog pronoun resolution system. Our system is intended as a com- ponent in an extractive dialog summarization sys- tem. There are several ways in which coreference in- formation can be integrated into extractive summa- rization. Kabadjov et al. (2005) e.g. obtained their best extraction results by specifying …

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