Building a large-scale knowledge base for machine translation
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
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EuroWordNet: a multilingual database with lexical semantic networks
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Computational Linguistics
Pattern Classification (2nd Edition)
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Yago: a core of semantic knowledge
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CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
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Uby: a large-scale unified lexical-semantic resource based on LMF
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Language Resources and Evaluation
UWN: a large multilingual lexical knowledge base
ACL '12 Proceedings of the ACL 2012 System Demonstrations
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Artificial Intelligence
YAGO2: A spatially and temporally enhanced knowledge base from Wikipedia
Artificial Intelligence
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IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Lexical databases are invaluable sources of knowledge about words and their meanings, with numerous applications in areas like NLP, IR, and AI. We propose a methodology for the automatic construction of a large-scale multilingual lexical database where words of many languages are hierarchically organized in terms of their meanings and their semantic relations to other words. This resource is bootstrapped from WordNet, a well-known English-language resource. Our approach extends WordNet with around 1.5 million meaning links for 800,000 words in over 200 languages, drawing on evidence extracted from a variety of resources including existing (monolingual) wordnets, (mostly bilingual) translation dictionaries, and parallel corpora. Graph-based scoring functions and statistical learning techniques are used to iteratively integrate this information and build an output graph. Experiments show that this wordnet has a high level of precision and coverage, and that it can be useful in applied tasks such as cross-lingual text classification.