Experiments in multi-modal automatic content extraction

HLT '01: Proceedings of the first international conference on Human language technology research(2001)

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摘要
Unlike earlier information extraction research programs, the new ACE (Automatic Content Extraction) program calls for entity extraction by identifying and linking all of the mentions of an entity in the source text, including names, descriptions, and pronouns. Coreference is therefore a key component. BBN has developed statistical co-reference models for this task, including one for pronoun co-reference that we describe here in some detail. In addition, ACE calls for extraction not just from clean text, but also from noisy speech and OCR input. Since speech recognizer output includes neither case nor punctuation, we have extended our statistical parser to perform sentence breaking integrated with parsing in a probabilistic model.
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关键词
statistical co-reference model,earlier information extraction research,clean text,entity extraction,speech recognizer output,noisy speech,source text,new ace,multi-modal automatic content extraction,statistical parser,pronoun co-reference,information extraction,probabilistic model,reference model
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