Sentential Structure and Discourse Parsing

Sentential Structure and Discourse Parsing Livia Polanyi, Chris Culy, Martin van den Berg, Gian Lorenzo Thione, David Ahn1 FX Palo Alto Laboratory 3400 Hillview Ave, Bldg. 4 Palo Alto, CA 94304 {polanyi|culy|vdberg|thione}@fxpal.com, ahn@science.uva.nl Abstract 1 In this paper, we describe how the LIDAS System (Linguistic Discourse Analysis Sys- tem), a discourse parser built as an implemen- tation of the Unified Linguistic Discourse Model (U-LDM) uses information from sen- tential syntax and semantics along with lexical semantic information to build the Open Right Discourse Parse Tree (DPT) that serves as a representation of the structure of the discourse (Polanyi et al., 2004; Thione 2004a,b). More specifically, we discuss how discourse seg- mentation, sentence-level discourse parsing, and text-level discourse parsing depend on the relationship between sentential syntax and dis- course. Specific discourse rules that use syn- tactic information are used to identify possible attachment points and attachment relations for each Basic Discourse Unit to the DPT. 1 Introduction In this paper, we describe discourse parsing under the Unified Linguistic Discourse Model (U-LDM) (Polanyi et al. 2004). In particular, we describe the relationship between the output of sentential pars- ing and discourse processing. The goal of discourse parsing under the U-LDM is to assign a proper semantic interpretation to every utterance in a text. In order to do so, the model constructs a structural representation of rela- tions among the discourse segments that constitute a text. This representation is realized as a Dis- course Parse Tree (DPT). Incoming discourse ut- terances are matched with the informational con- text needed for interpretation, and attached to nodes on the right edge of the tree. 1 Current address: Language and Inference Technology Group, Informatics Institute Kruislaan 403 1098 SJ Amsterdam, The Netherlands 1.1 Discourse Parse Tree The U-LDM builds upon the insights and mecha- nisms of the Linguistic Discourse Model (LDM) (Polanyi 1988). The DPT specifies which segments are coordinated to one another (bear a similar rela- tionship to a common higher order construct), which are subordinated to other constituents (give more information about entities or situations de- scribed in that constituent, or, alternatively, inter- rupt the flow of the discourse to interject unrelated information), and which are related as constituents of logical, language specific, rhetorical, genre spe- cific or interactional structures (n-ary relations). Importantly, the representation identifies which constituents are available for continuation at any moment in the development of a text and which are no longer structurally accessible. 1.2 Discourse Parsing While full understanding of the meaning of con- stituent utterances, world knowledge, inference and complex reasoning are needed to create the correct Discourse Parse Tree to represent the struc- ture of discourse under the LDM, in developing the U-LDM, it became apparent that most of the in- formation needed to assign structural relations to a text can be recovered from relating lexical, syntac- tic and semantic information in constituent sen- tences to information available at nodes on the DPT. Largely formal methods involving manipu- lating information in lexical ontologies and the output of …

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