2026-09-19T16:23:37Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/331412022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Boris Katz.
Fernandes, Aaron D. (Aaron David)
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2006-06-19T17:44:51Z
2006-06-19T17:44:51Z
2004
2004
http://hdl.handle.net/1721.1/33141
62242506
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (p. 75-77).
Most question answering systems narrow down their search space by issuing a boolean IR query on a keyword indexed corpus. This technique often proves futile for definitional questions, because they only contain one keyword or name. Thus, an IR search for only that term is likely to produce many spurious results; documents that contain mentions of the keyword, but not in a definitional context. An alternative approach is to glean the corpus in pre-processing for syntactic constructs in which entities are defined. In this thesis, I describe a regular expression language for detecting such constructs, with the help of a part-of-speech tagger and a named-entity recognizer. My system, named CoL. ForBIN, extracts entities and their definitions, and stores them in a database. This reduces the task of definitional question answering to a simple database lookup.
by Aaron D. Fernandes.
M.Eng.
77 p.
3310557 bytes
3313824 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Answering definitional questions before they are asked
Thesis
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<Abstract>Most question answering systems narrow down their search space by issuing a boolean IR query on a keyword indexed corpus. This technique often proves futile for definitional questions, because they only contain one keyword or name. Thus, an IR search for only that term is likely to produce many spurious results; documents that contain mentions of the keyword, but not in a definitional context. An alternative approach is to glean the corpus in pre-processing for syntactic constructs in which entities are defined. In this thesis, I describe a regular expression language for detecting such constructs, with the help of a part-of-speech tagger and a named-entity recognizer. My system, named CoL. ForBIN, extracts entities and their definitions, and stores them in a database. This reduces the task of definitional question answering to a simple database lookup.</Abstract>
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