Experiments in multi-modal automatic content extraction

Authors:
Lance Ramshaw;Elizabeth Boschee;Sergey Bratus;Scott Miller;Rebecca Stone;Ralph Weischedel;Alex Zamanian
Affiliations:
BBN Technologies, Cambridge, MA;BBN Technologies, Cambridge, MA;BBN Technologies, Cambridge, MA;BBN Technologies, Cambridge, MA;BBN Technologies, Cambridge, MA;BBN Technologies, Cambridge, MA;BBN Technologies, Cambridge, MA
Venue:
HLT '01 Proceedings of the first international conference on Human language technology research
Year:
2001

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Abstract

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.