Cross-Lingual Bootstrapping of Semantic Lexicons: The Case of FrameNet

Sebastian Padó, Maria Lapata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

This paper considers the problem of unsupervised semantic lexicon acquisition. We introduce a fully automatic approach which exploits parallel corpora, relies on shallow text properties, and is relatively inexpensive. Given the English FrameNet lexicon, our method exploits word alignments to generate frame candidate list for new languages, which are subsequently pruned automatically using a small set of linguistically motivated filters. Evaluation shows that our approach can produce high-precision multilingual FrameNet lexicons without recourse to bilingual dictionaries or deep syntactic and semantic analysis.
Original languageEnglish
Title of host publicationProceedings, The Twentieth National Conference on Artificial Intelligence and the Seventeenth Innovative Applications of Artificial Intelligence Conference
PublisherAAAI Press
Number of pages6
Publication statusPublished - 2005


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