By Richard Sproat (auth.), Elisabete Ranchhod, Nuno J. Mamede (eds.)
This publication constitutes the refereed complaints of the 3rd foreign convention PorTAL 2002 - Portugal for ordinary Language Processing, held in Faro, Portugal, in June 2002.
The 23 reviewed normal papers and eleven brief papers offered have been conscientiously reviewed and chosen from forty eight submissions. The papers are geared up in topical sections on pragmatics, discourse, semantics, and the lexicon; analyzing and producing spoken and written language; language-oriented info retrieval, query answering, summarization, and knowledge extraction; language-oriented desktop studying; multi-lingual processing, desktop translation, and translation aids; typical language interfaces and discussion platforms; instruments and assets; and evaluate of platforms.
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Extra info for Advances in Natural Language Processing: Third International Conference, PorTAL 2002 Faro, Portugal, June 23–26, 2002 Proceedings
Then, on the basis of this study, we shall describe how to build locative grammars with LGMs and graphs. Finally, we apply these grammars to journalistic corpora and evaluate the results. Table 1. Notations S NP PP Vsup Ni Prep Loc Det, Det1 E UN LE POSS Sentence Noun Phrase Prepositional Phrase Support verb ith nominal argument of a predicate (where i is an integer) Preposition Locative Preposition Determiners Empty element The singular indefinite determiners un or une (a or an) le, la (the) Possessive determiner 2 A Brief Linguistic Study This linguistic study is limited to a few properties to clarify the paper.
Table 2 shows the results obtained for several selected combinations of features, in order to establish the gain in accuracy when new features are incorporated in the training. The ﬁrst row (labelled as “M F S”) is the base-value against which the remainder of the feature selections are measured to show the gain or loss in accuracy. 4% more than MFS). Again, nouns obtain better results than verbs. Table 3 shows the evaluation of these last set of features on each word. ME were also evaluated with the train and test data from SENSEVAL-2 for the Spanish lexical sample task.
Maximum Entropy Models for Natural Language Ambiguity Resolution. PhD thesis, University of Pennsylvania (1998) 10. : Dependency-based evaluation of minipar. In: Proceedings of the Workshop on the Evaluation of Parsing Systems, First International Conference on Language Resources and Evaluation, Granada, Spain (1998) 11. : Integrating multiple knowledge sources to disambiguate word senses: An exemplar-based approach. : Proceedings of the Thirty-Fourth Annual Meeting of the Association for Computational Linguistics, San Francisco, Morgan Kaufmann Publishers (1996) 12.
Advances in Natural Language Processing: Third International Conference, PorTAL 2002 Faro, Portugal, June 23–26, 2002 Proceedings by Richard Sproat (auth.), Elisabete Ranchhod, Nuno J. Mamede (eds.)