Kim, Su Nam and Timothy Baldwin (2007) Disambiguating Noun Compounds, In Proceedings of the Twenty-Second Conference on Artificial Intelligence (AAAI-07), Vancouver, Canada, pp. 901-6

نویسندگان

  • Su Nam Kim
  • Timothy Baldwin
چکیده

This paper is concerned with the interaction between word sense disambiguation and the interpretation of noun compounds (NCs) in English. We develop techniques for disambiguating word sense specifically in NCs, and then investigate whether word sense information can aid in the semantic relation interpretation of NCs. To disambiguate word sense, we combine the one sense per collocation heuristic with the grammatical role of polysemous nouns and analysis of word sense combinatorics. We built supervised and unsupervised classifiers for the task and demonstrate that the supervised methods are superior to a number of baselines and also a benchmark state-of-the-art WSD system. Finally, we show that WSD can significantly improve the accuracy of NC interpretation.

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Disambiguating Noun Compounds

This paper is concerned with the interaction between word sense disambiguation and the interpretation of noun compounds (NCs) in English. We develop techniques for disambiguating word sense specifically in NCs, and then investigate whether word sense information can aid in the semantic relation interpretation of NCs. To disambiguate word sense, we combine the one sense per collocation heuristic...

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Kim, Su Nam and Timothy Baldwin (2008) Benchmarking Noun Compound Interpretation, In Proceedings of the Third International Joint Conference on Natural Language Processing (IJCNLP 2008), Hyderabad, India

In this paper we provide benchmark results for two classes of methods used in interpreting noun compounds (NCs): semantic similarity-based methods and their hybrids. We evaluate the methods using 7-way and binary class data from the nominal pair interpretation task of SEMEVAL-2007.1 We summarize and analyse our results, with the intention of providing a framework for benchmarking future researc...

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This paper proposes an unsupervised approach to automatically interpret noun compounds using semantic similarity. Our proposed unsupervised method is based on obtaining a large amount of robust evidence for NC interpretation. In order to obtain evidence sentences for semantic relations (SRs), we first acquired sentences containing both a head noun and its modifier in the form of SR definitions....

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تاریخ انتشار 2007