Resolving Ellipsis in Clarification

35309

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nan

Abstract

We offer a computational analysis of the resolution of ellipsis in certain cases of dialogue clarification. We show that this goes beyond standard techniques used in anaphora and ellipsis resolu- tion and requires operations on highly structured, linguistically heterogeneous representations. We characterize these operations and the representations on which they operate. We offer an analy- sis couched in a version of Head-Driven Phrase Structure Grammar combined with a theory of information states (IS) in dialogue. We sketch an algorithm for the process of utterance integration in ISs which leads to grounding or clarifi- cation. 1

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Resolving Ellipsis in Clarification Jonathan Ginzburg Dept of Computer Science King’s College, London The Strand, London WC2R 2LS UK ginzburg@dcs.kcl.ac.uk Robin Cooper Dept of Linguistics G¨oteborg University Box 200, 405 30 G¨oteborg, Sweden cooper@ling.gu.se Abstract We offer a computational analysis of the resolution of ellipsis in certain cases of dialogue clarification. We show that this goes beyond standard techniques used in anaphora and ellipsis resolu- tion and requires operations on highly structured, linguistically heterogeneous representations. We characterize these operations and the representations on which they operate. We offer an analy- sis couched in a version of Head-Driven Phrase Structure Grammar combined with a theory of information states (IS) in dialogue. We sketch an algorithm for the process of utterance integration in ISs which leads to grounding or clarifi- cation. 1 Introduction Clarification ellipsis (CE), nonsentential ellipti- cal queries such as (1a(i),(ii)) are commonplace in human conversation. Two common read- ings/understandings of CE are exemplified in (1b,c): the clausal reading is commonly used sim- ply to confirm the content of a particular subutter- ance. The main function of the constituent read- ing is to elicit an alternative description or osten- sion to the content (referent or predicate etc) in- tended by the original speaker of the reprised sub- utterance. (1) a. A: Did Bo finagle a raise? B: (i) Bo?/ (ii) finagle? b. Clausal reading: Are you asking if BO (of all people) finagled a raise/Bo FI- c.NAGLED a raise (of all actions) Constituent reading: Bo?/What does it mean to finagle?Who is The issue of whether CE involves an ambi- guity or is simply vague is an important one.1 � 2 Clearly, pragmatic reasoning plays an important role in understanding CEs. Some considerations do, nonetheless, favour the existence of an ambi- guity. First, the BNC provides numerous exam- ples of misunderstandings concerning CE inter- pretation,3 where a speaker intends one reading, is misunderstood, and clarifies his original inter- pretation: (2) a. A: ... you always had er er say every foot he had with a piece of spunyarn in the wire/B: Spunyarn?/A: Spunyarn, yes/B: What’s spunyarn? b. A: Have a laugh and joke with Dick./ B: Dick?/A: Have a laugh and joke with Dick./B: Who’s Dick? 1An anonymous ACL reviewer proposed to us that all CE could be analyzed in terms of a single reading along the lines of “I thought I heard you say Bo, and I don’t know why you would do so?”. 2Closely related to this issue is the issue of what other readings/understandings CE exhibits. We defer discussion of the latter issue to (Purver et al., 2001), which provides a detailed analysis of the frequency of CEs and their under- standings among clarification utterances in the British Na- tional Corpus (BNC). 3This confirms our (non-instrumentally tested) impres- sion that these understandings are not on the whole disam- biguated intonationally. All our CE data from the BNC was found using SCoRE, Matt Purver’s dialogue oriented BNC search engine (Purver, 2001). More crucially, the clausal and constituent readings involve …

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Labeled Text

We offer a computational analysis of the resolution of ellipsis in certain cases of dialogue clarification. We show that this goes beyond standard techniques used in anaphora and ellipsis resolution and requires operations on highly structured, linguistically heterogeneous representations. We characterize these operations and the representations on which they operate. We offer an analysis couched in a version of Head-Driven Phrase Structure Grammar combined with a theory of information states (IS) in dialogue. We sketch an algorithm for the process of utterance integration in ISs which leads to grounding or clarification. 1

Publication Details

Paper ID:
35309
Year:
2001
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan