Extraction of semantic relations from a Basque monolingual dictionary using Constraint Grammar

  1. Agirre Bengoa, Eneko
  2. Ansa Osteriz, Olatz
  3. Arregi Iparragirre, Xabier
  4. Artola Zubillaga, Xabier
  5. Díaz de Ilarraza Sánchez, Arantza
  6. Lersundi Ayestaran, Mikel
  7. Martínez Iraola, David
  8. Sarasola Gabiola, Kepa
  9. Urízar Enbeitia, Rubén
Livre:
Proceedings of the Ninth EURALEX International Congress, EURALEX 2000: Stuttgart, Germany, August 8th - 12th, 2000
  1. Heid, Ulrich (ed. lit.)
  2. Evert, Stefan (ed. lit.)
  3. Lehmann, Egbert (ed. lit.)
  4. Rohrer, Christian (ed. lit.)

Éditorial: Stuttgart : Institut für Maschinelle Sprachverarbeitung, Universität Stuttgart, 2000

Année de publication: 2000

Pages: 641-650

Congreso: EURALEX. International Congress (9. 2000. Stuttgart)

Type: Communication dans un congrès

Résumé

This paper deals with the exploitation of dictionaries for the semi-automatic construction of lexicons and lexical knowledge bases. The final goal of our research is to enrich the Basque Lexical Database with semantic information such as senses, definitions, semantic relations, etc., extracted from a Basque monolingual dictionary. The work here presented focuses on the extraction of the semantic relations that best characterise the headword, that is, those of synonymy, antonymy, hypernymy, and other relations marked by specific relators and derivation. All nominal, verbal and adjectival entries were treated. Basque uses morphological inflection to mark case, and therefore semantic relations have to be inferred from suffixes rather than from prepositions. Our approach combines a morphological analyser and surface syntax parsing (based on Constraint Grammar), and has proven very successful for highly inflected languages such as Basque. Both the effort to write the rules and the actual processing time of the dictionary have been very low. At present we have extracted 42,533 relations, leaving only 2,943 (9%) definitions without any extracted relation. The error rate is extremely low, as only 2.2% of the extracted relations are wrong.