We define a back-and-forth translation between Hole Semantics and dominance constraints, two formalisms used in underspecified semantics. There are fundamental differences between the two, but we show that they disappear on practically useful descriptions. Our encoding bridges a gap between two underspecification formalisms, and speeds up the processing of Hole Semantics.

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This paper presents intial work on a system that bridges from robust, broad-coverage natural language processing to precise semantics and automated reasoning, focusing on solving logic puzzles drawn from sources such as the Law School Admission Test (LSAT) and the analytic section of the Graduate Record Exam (GRE). We highlight key challenges, and discuss the representations and performance of the prototype system.

This paper describes rudi ("Resolving Underspecification with Discourse Information"), a dialogue system component which computes automatically some aspects of the content of scheduling dialogues, particularly the intended denotation of the temporal expressions, the speech acts performed and the underlying goals. rudi has a number of nice features: it is a principled approximation of a logically precise and linguistically motivated framework for representing semantics and implicatures

Clarification requests are an important, relatively common and yet under-studied dialogue device allowing a user to ask about some feature (e.g. the meaning or form) of an utterance, or part thereof. They can take many different forms (often highly elliptical) and can have many different meanings (requesting various types of information). This thesis combines empirical, theoretical and implementational work to provide a study of the various types of clarification request that exist, give a theoretical analysis thereof, and show how the results can be applied to add useful capabilities to a prototype computational dialogue system. A series

This paper describes a method of interactively visualizing and directing the process of translating a sentence. The method allows a user to explore a model of syntax-based statistical machine translation (MT), to understand the model’s strengths and weaknesses, and to compare it to other MT systems. Using this visualization method, we can find and address conceptual and practical problems in an MT system. In our demonstration at ACL, new users of our tool will drive a syntaxbased decoder for themselves. 1

Abstract. We describe the automatic acquisition of a lexicon of verb subcategorisations from a domain-specific corpus, and an evaluation of the impact this lexicon has on the performance of a “deep”, HPSG parser of English. We conducted two experiments to determine whether the empirically extracted verb stems would enhance the lexical coverage of the grammar and to see whether the automatically extracted verb subcategorisations would result in enhanced parser coverage. In our experiments, the empirically extracted verbs enhance lexical coverage by 8.5%. The automatically extracted verb subcategorisations enhance the parse success rate by 15 % in theoretical terms and by 4.5 % in practice. This is a promising approach for improving the robustness of deep parsing. 1

Past approaches to developing an effective lexicon component in a grammar development environment have suffered from a number of usability and efficiency issues. We present a lexical database module currently in use by a number of grammar development projects. The database module presented addresses issues which have caused problems in the past and the power of a database architecture provides a number of practical advantages as well as a solid framework for future extension. 1.

Abstract. In this paper we introduce XMG1 (eXtensible MetaGrammar), a system dedicated to the production of wide coverage lexicalised grammars. In particular, we show that XMG provides a representation language suitable for describing different linguistic dimensions and different grammatical formalisms. Furthermore, we briefly sketch the architecture of the XMG compiler showing that it encodes a theoretically sound processing of the XMG formalism. 1

In this paper, we present a definition of unification of weighted feature structures designed to deal with constraint relaxation. The application of phrase structure rules in a unification-based Natural Language Processing system is adapted such that inconsistent values do not lead to failure, but are penalised. These penalties are based on the signature and the shape of the feature structures, and thus realise an elegant and general approach to relaxation.