Introduction to Biomedical Named Entity Recognition
Toyota Technological Institute
Studies on Named Entity Recognition (NER) became active in the 1980s. The target of NER at that time was mainly proper nouns, such as person and corporate names, and numerical expressions, such as date and percentage. Since the 1990s, categories of the names targeted by NER have widened to technical terms, such as gene/protein names.
NER techniques are important because a lot of names are ambiguous and it is necessary to disambiguate them to handle the content of text at the semantic level. For example, "Washington" could be used for both a person name and a location name. NER tools decide named entity categories of the ambiguous names. For example, NER identifies that "Washington" is a person name in "We obtained new data from Mr. Washington." Without this step, computerized systems cannot decide whether "Washington" in the text should be treated as a contact point or a source point of the action. NER for biomedical terms is much harder to accomplish because many terms conflict with general English words, e.g, "cat" is a protein name, and with other named entity categories, e.g. "ER" is a protein name.
JNLPBA-2004 Shared Task data
Yutaka Sasaki, Yoshimasa Tsuruoka, John McNaught, and Sophia Ananiadou,
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9(Suppl 11):S5, 2008.(HTML)
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(C)2009 Yutaka Sasaki
Last update: 15 Dec 2009