A method for extracting causal knowledge from textual databases
This paper describes the first phase of a project to develop a knowledge extraction and knowledge discovery system that extracts causal knowledge from a textual database automatically, and attempts to infer new causal relationships from the extracted information. The initial work is focused on d...
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| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/101369 http://hdl.handle.net/10220/18370 http://www.connexor.com/nlplib/?q=node/540 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | This paper describes the first phase of a project to develop a
knowledge extraction and knowledge discovery system that extracts
causal knowledge from a textual database automatically, and
attempts to infer new causal relationships from the extracted information.
The initial work is focused on developing an automatic
method for identifying and extracting cause-effect information expressed
in medical abstracts. Linguistic clues that indicate the presence
of a causal relation in text are being identified, and linguistic
patterns constructed to represent the different ways in which cause
and effect are expressed in English sentences. The linguistic patterns
have “slots” that indicate the parts of the sentence representing
the cause and the effect. The information extraction process
involves matching the linguistic patterns with the syntactic structure
of sentences, and extracting the parts of the sentence that
match with the slots in the patterns. The extracted information is
stored in a structured manner in a “cause-effect template” that indicates
the different roles and attributes of the causal situation described
in the text. |
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