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- W2555368418 abstract "In order to let computers understand text, identifying various types of relations in the text is a necessary step. In natural language processing (NLP), case frames are a very essential knowledge base which represents the relations between a predicate and its arguments. Case frames can support various types of NLP applications, such as parsing, machine translation, recognizing textual entailment and paraphrasing. For instance, in the classical example of parsing, “saw a girl with a telescope,” there is an ambiguity problem of which argument the prepositional phrase, “with a telescope,” is modifying. It would be easy to judge that the prepositional phrase belongs to the verb if knowledge of a case frame “see someone/something with telescope,” is available. For NLP applications in multiple languages and multilingual applications, compilation of large-scale case frames in these languages is important. Manually compiling this kind of knowledge in multiple languages would be too costly and would be limited by low coverage. In this paper, we propose a framework for automatically constructing case frames in multiple languages. In this framework, we extract reliable predicate-argument structures from large corpora by small sets of linguistic rules specific to each language, and apply clustering to produce case frames. Even though the grammars in different languages are quite dissimilar, we show that extracting predicate-argument structures to build case frames is achieved by one common way. In practice, we construct case frames of Chinese and English." @default.
- W2555368418 created "2016-11-30" @default.
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- W2555368418 date "2012-01-01" @default.
- W2555368418 modified "2023-09-26" @default.
- W2555368418 title "A Framework of Automatic Case Frame Construction From a Raw Corpus" @default.
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