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- item-1 hasContent marie-jeanne-derouin.
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- item-2 hasContent andre-le-meur.
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- 191 creator hiroaki-sato.
- 191 type InProceedings.
- 191 label "New Functions of FrameSQL for Multilingual FrameNets".
- 191 sameAs 191.
- 191 abstract "The Berkeley FrameNet Project (BFN) is making an English lexical database called FrameNet, which describes syntactic and semantic properties of an English lexicon extracted from large electronic text corpora (Baker et al., 1998). Other projects dealing with Spanish, German and Japanese follow a similar approach and annotate large corpora. FrameSQL is a web-based application developed by the author, and it allows the user to search the BFN database in a variety of ways (Sato, 2003). FrameSQL shows a clear view of the headword s grammar and combinatorial properties offered by the FrameNet database. FrameSQL has been developing and new functions were implemented for processing the Spanish FrameNet data (Subirats and Sato, 2004). FrameSQL is also in the process of incorporating the data of the Japanese FrameNet Project (Ohara et al., 2003) and that of the Saarbrücken Lexical Semantics Acquisition Project (Erk et al., 2003) into the database and will offer the same user-interface for searching these lexical data. This paper describes new functions of FrameSQL, showing how FrameSQL deals with the lexical data of English, Spanish, Japanese and German seamlessly.".
- 191 hasAuthorList authorList.
- 191 hasTopic Linguistics.
- 191 isPartOf proceedings.
- 191 keyword "Lexicon, lexical database".
- 191 keyword "Multilinguality".
- 191 keyword "Semantics".
- 191 title "New Functions of FrameSQL for Multilingual FrameNets".
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- item-1 hasContent hiroaki-sato.
- 192 creator adrian-iftene.
- 192 creator alexandra-balahur-dobrescu.
- 192 type InProceedings.
- 192 label "Named Entity Relation Mining using Wikipedia".
- 192 sameAs 192.
- 192 abstract "Discovering relations among Named Entities (NEs) from large corpora is both a challenging, as well as useful task in the domain of Natural Language Processing, with applications in Information Retrieval (IR), Summarization (SUM), Question Answering (QA) and Textual Entailment (TE). The work we present resulted from the attempt to solve practical issues we were confronted with while building systems for the tasks of Textual Entailment Recognition and Question Answering, respectively. The approach consists in applying grammar induced extraction patterns on a large corpus - Wikipedia - for the extraction of relations between a given Named Entity and other Named Entities. The results obtained are high in precision, determining a reliable and useful application of the built resource.".
- 192 hasAuthorList authorList.
- 192 hasTopic Linguistics.
- 192 isPartOf proceedings.
- 192 keyword "Grammars".
- 192 keyword "Information Extraction, Information Retrieval".
- 192 keyword "Text mining".
- 192 title "Named Entity Relation Mining using Wikipedia".
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- item-1 hasContent adrian-iftene.
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- item-2 hasContent alexandra-balahur-dobrescu.
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- 193 creator frederic-bechet.
- 193 creator georges-linares.
- 193 creator stanislas-oger.
- 193 type InProceedings.
- 193 label "Local Methods for On-Demand Out-of-Vocabulary Word Retrieval".
- 193 sameAs 193.
- 193 abstract "Most of the Web-based methods for lexicon augmenting consist in capturing global semantic features of the targeted domain in order to collect relevant documents from the Web. We suggest that the local context of the out-of-vocabulary (OOV) words contains relevant information on the OOV words. With this information, we propose to use the Web to build locally-augmented lexicons which are used in a final local decoding pass. First, an automatic web based OOV word detection method is proposed. Then, we demonstrate the relevance of the Web for the OOV word retrieval. Different methods are proposed to retrieve the hypothesis words. We finally retrieve about 26% of the OOV words with a lexicon increase of less than 1000 words using the reference context.".
- 193 hasAuthorList authorList.
- 193 hasTopic Linguistics.
- 193 isPartOf proceedings.
- 193 keyword "Language modelling".
- 193 keyword "Lexicon, lexical database".
- 193 keyword "Speech recognition and understanding".
- 193 title "Local Methods for On-Demand Out-of-Vocabulary Word Retrieval".
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- item-1 hasContent stanislas-oger.
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- item-3 hasContent frederic-bechet.
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- 197 creator david-griol.
- 197 creator emilio-sanchis.
- 197 creator encarna-segarra.
- 197 creator lluis-f-hurtado.
- 197 type InProceedings.
- 197 label "Acquisition and Evaluation of a Dialog Corpus through WOz and Dialog Simulation Techniques".
- 197 sameAs 197.
- 197 abstract "In this paper, we present a comparison between two corpora acquired by means of two different techniques. The first corpus was acquired by means of the Wizard of Oz technique. A dialog simulation technique has been developed for the acquisition of the second corpus. A random selection of the user and system turns has been used, defining stop conditions for automatically deciding if the simulated dialog is successful or not. We use several evaluation measures proposed in previous research to compare between our two acquired corpora, and then discuss the similarities and differences between the two corpora with regard to these measures.".
- 197 hasAuthorList authorList.
- 197 hasTopic Linguistics.
- 197 isPartOf proceedings.
- 197 keyword "Acquisition, Machine Learning".
- 197 keyword "Corpus (creation, annotation, etc.)".
- 197 keyword "Dialogue & Natural Interactivity".
- 197 title "Acquisition and Evaluation of a Dialog Corpus through WOz and Dialog Simulation Techniques".
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