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Báo cáo khoa học: "Automatic of Proper Processing Names in Texts"

This paper shows first the problems raised by proper names in natural language processing. Second, it introduces the knowledge representation structure we use based on conceptual graphs. Then it explains the techniques which are used to process known and unknown proper names. At last, it gives the performance of the system and the further works we intend to deal with. | Automatic Processing of Proper Names in Texts Francis Wolinski1 2 Frantz Vichot1 Bruno Dillet1 1 Informatique CDC 2 LAFORIA Caisse des Depots et Consignations Université de Paris VI France France E-mail wolinski vichot dillet @icdc.fr Abstract This paper shows first the problems raised by proper names in natural language processing. Second it introduces the knowledge representation structure we use based on conceptual graphs. Then it explains the techniques which are used to process known and unknown proper names. At last it gives the performance of the system and the further works we intend to deal with. 1 Introduction The Exoseme system 6 7 is an operational application which continuously analyses the economic flow from Agence France Presse AFP . AFP which covers the current economic life of the major industrialised countries transmits on average 400 dispatches per day on this flow. Their content is drafted in French in a journalistic style. Using this flow Exoseme feeds various users concerning precise and varied subjects for example rating announcements company results acquisitions sectors of activity observation of competition partners or clients etc. 50 such themes have currently been developed. They rely on precise filtering of dispatches with highlighting of sentences for fast reading. Exoseme is composed of several modules a morphological analyser a proper name module a syntactical analyser a semantic analyser and a filtering module. The proper name module has two goals segmenting and categorising proper names. During the whole processing of a dispatch the proper name module is involved in three different steps. First it segments proper names during the morphological analysis. Second it categorises proper names during the semantic analysis. Third it is invoked by the filtering module to supply some more information needed for routing the dispatch. The proper name module is based on different techniques which are used to detect and categorise proper names .