Extracting noun phrases for all of MEDLINE.
- 1 January 1999
- journal article
- p. 671-5
Abstract
A natural language parser that could extract noun phrases for all medical texts would be of great utility in analyzing content for information retrieval. We discuss the extraction of noun phrases from MEDLINE, using a general parser not tuned specifically for any medical domain. The noun phrase extractor is made up of three modules: tokenization; part-of-speech tagging; noun phrase identification. Using our program, we extracted noun phrases from the entire MEDLINE collection, encompassing 9.3 million abstracts. Over 270 million noun phrases were generated, of which 45 million were unique. The quality of these phrases was evaluated by examining all phrases from a sample collection of abstracts. The precision and recall of the phrases from our general parser compared favorably with those from three other parsers we had previously evaluated. We are continuing to improve our parser and evaluate our claim that a generic parser can effectively extract all the different phrases across the entire medical literature.This publication has 7 references indexed in Scilit:
- Taming MEDLINE With Concept SpacesScience, 1998
- Validation of clinical problems using a UMLS-based semantic parser.1998
- Information Retrieval in Digital Libraries: Bringing Search to the NetScience, 1997
- Associating semantic grammars with the SNOMED: processing medical language and representing clinical facts into a language-independent frame.1995
- A General Natural-language Text Processor for Clinical RadiologyJournal of the American Medical Informatics Association, 1994
- Computer auditing of surgical operative reports written in English.1993
- Extending a natural language parser with UMLS knowledge.1991