Coordinate Noun Phrase Disambiguation in a Generative Parsing Model

Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pages 680–687, Prague, Czech Republic, June 2007. c⃝2007 Association for Computational Linguistics Coordinate Noun Phrase Disambiguation in a Generative Parsing Model Deirdre Hogan∗ Computer Science Department Trinity College Dublin Dublin 2, Ireland dhogan@computing.dcu.ie Abstract In this paper we present methods for im- proving the disambiguation of noun phrase (NP) coordination within the framework of a lexicalised history-based parsing model. As well as reducing noise in the data, we look at modelling two main sources of information for disambiguation: symmetry in conjunct structure, and the dependency between con- junct lexical heads. Our changes to the base- line model result in an increase in NP coor- dination dependency f-score from 69.9% to 73.8%, which represents a relative reduction in f-score error of 13%. 1 Introduction Coordination disambiguation is a relatively little studied area, yet the correct bracketing of coordina- tion constructions is one of the most difficult prob- lems for natural language parsers. In the Collins parser (Collins, 1999), for example, dependencies involving coordination achieve an f-score as low as 61.8%, by far the worst performance of all depen- dency types. Take the phrase busloads of executives and their wives (taken from the WSJ treebank). The coordi- nating conjunction (CC) and and the noun phrase their wives could attach to the noun phrase exec- utives, as illustrated in Tree 1, Figure 1. Alterna- tively, their wives could be incorrectly conjoined to the noun phrase busloads of executives as in Tree 2, Figure 1. ∗ Now at the National Centre for Language Technology, Dublin City University, Ireland. As with PP attachment, most previous attempts at tackling coordination as a subproblem of parsing have treated it as a separate task to parsing and it is not always obvious how to integrate the methods proposed for disambiguation into existing parsing models. We therefore approach coordination disam- biguation, not as a separate task, but from within the framework of a generative parsing model. As noun phrase coordination accounts for over 50% of coordination dependency error in our base- line model we focus on NP coordination. Us- ing a model based on the generative parsing model of (Collins, 1999) Model 1, we attempt to improve the ability of the parsing model to make the correct coordination decisions. This is done in the context of parse reranking, where the n-best parses output from Bikel’s parser (Bikel, 2004) are reranked ac- cording to a generative history-based model. In Section 2 we summarise previous work on co- ordination disambiguation. There is often a consid- erable bias toward symmetry in the syntactic struc- ture of two conjuncts and in Section 3 we introduce new parameter classes to allow the model to prefer symmetry in conjunct structure. Section 4 is con- cerned with modelling the dependency between con- junct head words and begins by looking at how the different handling of coordination in noun phrases and base noun phrases (NPB) affects coordination disambiguation.1 We look at how we might improve …

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