Automatic Mapping Clinical Notes to Medical - RMIT University

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who [u : np] WH(np, s, s/?gq) λP.λQ.(Q P ) 1 saw (np\s)/np [z : np] 2 [/E] saw ◦ np ⊢ np\s [\E] np ◦ (saw ◦ np) ⊢ s ((see z) u) [WH]1 who ◦ (saw ◦ np) ⊢ s/?gq λQ.(Q λu.((see z) u)) who ◦ (saw ◦ np) ⊢ s/?np [lowering] λu.((see z) u) [WHin]2 who ◦ (saw ◦ whom) ⊢ (s/?np)/?np λx.λy.((λz.λu.((see z) u) y) x) ❀∗ β λx.λy.((see y) x) whom WHin(np, s/?np, (s/?np)/?np) λP λx.λy.((P y) x) of the question-answer sequence and B is the type of the answer. With the syntactic decomposition of wh-types, we have been able to express the semantic decomposition of the semantic ω-operator as a λ-term. Additionally, the syntactic and semantic decomposition of the type for wh-questions leads to a derivability pattern of wh-type schemata. This pattern provides generalizations for different question answer sequences. For instance, the difference between wh-pronouns and wh-determiners and the derivation of multiple wh-questions. The presented sentences have been computed using the on-line parser for type-logical grammars. See http://grail.let.uu.nl/~vermaat for further analyses of this specific grammar fragment and that of other languages. The theoretical results in this paper have been limited to argument wh-phrases. Next step is to see how the derivability schema and the wh-type schema apply to other types of wh-phrases, such as adverbial wh-phrases. Additionally, we would like to investigate additional logical axioms that may lead to further generalizations for natural language analysis. For a practical purpose, it would be interesting to see whether the theoretical issues addressed in this paper could be used in existing question-answer dialogue systems, for example to validate the answer. Acknowledgments The Netherlands Organisation for Scientific Research (NWO) for providing the Rubicon grant. Figure 3: Derivation of multiple wh-question 112 References Raffaella Bernardi and Richard Moot. 2003. Generalized quantifiers in declarative and interrogative sentences. Logic Journal of the IGPL, 11(4):419–34. Jeroen Groenendijk and Martin Stokhof. 1984. Studies on the semantics of questions and the pragmatics of answers. Ph.D. thesis, University of Amsterdam. Jeroen Groenendijk and Martin Stokhof. 1997. Questions. In Johan van Benthem and Alice ter Meulen, editors, Handbook of Logic and Language, chapter 19, pages 1055–1124. Elsevier, Amsterdam. C.J. Hamblin. 1958. Questions. Australasian Journal of Philosophy, 36:159–68. Roland Hausser. 1983. The syntax and semantics of english mood. In Ferenc Kiefer, editor, Questions and Answers, pages 97–158. Reidel, Dordrecht. Henry Hi˙z. 1978. Difficult questions. In Henry Hi˙z, editor, Questions. Reidel, Dordrecht/Boston. Lauri Karttunen. 1977. Syntax and semantics of questions. Linguistics and Philosophy, 1:3–44. Manfred Krifka. 2001. For a structured meaning account of questions and answers. In C. Fery and W. Sternefeld, editors, Audiatur Vox Sapientia. A Festschrift for Arnim von Stechow, pages 287–319. Akademie Verlag, Berlin. Michael Moortgat. 1991. Generalized quantifiers and discontinuous type constructors. In W. Sijtsma and A. van Horck, editors, Discontinuous constituency. De Gruyter. Michael Moortgat. 1997. Categorial type logics. In Johan van Benthem and Alice ter Meulen, editors, Handbook of Logic and Language, chapter 2, pages 93–177. Elsevier, Amsterdam. Glyn Morrill. 1994. Type Logical Grammar. Categorial Logic of Signs. Kluwer, Dordrecht. Mark Steedman. 2000. The syntactic process. The MIT Press, Cambridge, MA. Willemijn Vermaat. 2006. The Logic of Variation: a Cross-linguistic account of Wh-question Formation in type-logical grammar. Ph.D. thesis, Utrecht University, UiL-OTS, January.
Towards the Evaluation of Referring Expression Generation Jette Viethen Centre for Language Technology Macquarie University Sydney NSW 2109 jviethen@ics.mq.edu.au Abstract The Natural Language Generation community is currently engaged in discussion as to whether and how to introduce one or several shared evaluation tasks, as are found in other fields of Natural Language Processing. As one of the most welldefined subtasks in NLG, the generation of referring expressions looks like a strong candidate for piloting such shared tasks. Based on our earlier evaluation of a number of existing algorithms for the generation of referring expressions, we explore in this paper some problems that arise in designing an evaluation task in this field, and try to identify general considerations that need to be met in evaluating generation subtasks. 1 Introduction In recent years, the inclusion of an evaluation component has become almost obligatory in any publication in the field of Natural Language Processing. For complete systems, user-based and taskoriented evaluation are almost standard practice in both the Natural Language Understanding (NLU) and Natural Language Generation (NLG) communities. A third, more competitive, form of evaluation has become increasingly popular in NLU in the form of shared-task evaluation campaigns (STECs). In a STEC, different approaches to a welldefined problem are compared based on their performance on the same task. A large number of different research communities within NLP, such as Question Answering, Machine Translation, Document Summarisation, Word Sense Disambiguation, and Information Retrieval, have adopted a Robert Dale Centre for Language Technology Macquarie University Sydney NSW 2109 robert.dale@mq.edu.au shared evaluation metric and in many cases a shared-task evaluation competition. The NLG community has so far withstood this trend towards a joint evaluation metric and a competitive evaluation task, but the idea has surfaced in a number of discussions, and most intensely at the 2006 International Natural Language Generation Conference (see, for example, Bangalore et al. (2000), Reiter and Sripada (2002), Reiter and Belz (2006), Belz and Reiter (2006), Belz and Kilgarriff (2006), Paris et al. (2006), and van Deemter et al. (2006)). Amongst the various component tasks that make up Natural Language Generation, the generation of referring expressions is probably the subtask for which there is the most agreement on problem definition; a significant body of work now exists in the development of algorithms for generating referring expressions, with almost all published contributions agreeing on the general characterisation of the task and what constitutes a solution. This suggests that, if formal shared tasks for NLG are to be developed, the generation of referring expressions is a very strong candidate. In (Viethen and Dale, 2006), we argued that the evaluation of referring expression generation algorithms against natural, human-generated data is of fundamental importance in assessing their usefulness for the generation of understandable, naturalsounding referring expressions. In this paper, we discuss a number of issues that arise from the evaluation carried out in (Viethen and Dale, 2006), and consider what these issues mean for any attempt to define a shared task in this area. The remainder of this paper has the following structure. In Section 2, we briefly describe the evaluation experiment we carried out for three well-established referring expression generation Proceedings of the 2006 Australasian Language Technology Workshop (ALTW2006), pages 113–120. 113
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Proceeding of the Australasian Lang
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Program Chairs: Committees Lawrence
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Towards the Evaluation of Referring
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TIME ACC COVER FAIL RATE % secs % %
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model. We explore different estimat
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acy. The difference in correctly as
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Experiments with Sentence Classific
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datasets with skewed distribution t
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words produced by the feature selec
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Sentence Class NB DT SVM Apology 1.
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Computational Semantics in the Natu
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Classifying Speech Acts using Verba
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ance. Several additional example ut
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our results. In classifying only th
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Extracting Patient Clinical Profile
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