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Pattern learning for event extraction using monolingual statistical machine translation.
| Content Provider | CiteSeerX |
|---|---|
| Author | Turchi, Marco Zavarella, Vanni Tanev, Hristo |
| Abstract | Event extraction systems typically take advantage of language and domain-specific knowledge bases, including patterns that are used to identify specific facts in text; techniques to acquire these patterns can be considered one of the most challenging issues. In this work, we propose a languageindependent and weakly-supervised algorithm to automatically discover linear patterns from texts. Our approach is based on a phrase-based statistical machine translation system trained on monolingual data. A bootstrapping version of the algorithm is proposed. Our method was tested on patterns with different domain-specific semantic roles in three languages: English, Spanish and Russian. Performance shows the feasibility of our approach and its capability of working with texts in various languages. 1 |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Pattern Learning Event Extraction Monolingual Statistical Machine Translation Event Extraction System Monolingual Data Challenging Issue Bootstrapping Version Linear Pattern Phrase-based Statistical Machine Translation System Specific Fact Different Domain-specific Semantic Role Domain-specific Knowledge Base Various Language Weakly-supervised Algorithm |
| Content Type | Text |
