Domain-independent information extraction in unstructured text

Technical Report · Sun Sep 01 04:00:00 EDT 1996

DOI:https://doi.org/10.2172/378821· OSTI ID:378821

Irwin, N H ^[1]

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1. Sandia National Labs., Albuquerque, NM (United States). Software Surety Dept.

Extracting information from unstructured text has become an important research area in recent years due to the large amount of text now electronically available. This status report describes the findings and work done during the second year of a two-year Laboratory Directed Research and Development Project. Building on the first-year`s work of identifying important entities, this report details techniques used to group words into semantic categories and to output templates containing selective document content. Using word profiles and category clustering derived during a training run, the time-consuming knowledge-building task can be avoided. Though the output still lacks in completeness when compared to systems with domain-specific knowledge bases, the results do look promising. The two approaches are compatible and could complement each other within the same system. Domain-independent approaches retain appeal as a system that adapts and learns will soon outpace a system with any amount of a priori knowledge.

• Research Organization: Sandia National Labs., Albuquerque, NM (United States)
• Sponsoring Organization: USDOE, Washington, DC (United States)
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 378821
• Report Number(s): SAND--96-2337; ON: DE96015325
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
COMPUTER NETWORKS
DOCUMENT TYPES
INFORMATION RETRIEVAL
INFORMATION SYSTEMS
LEISURE TIME ACTIVITIES
MEDICAL RECORDS
NATURAL LANGUAGE
TREATIES