Title
Learning Word Syntactic Subcategorizations Interactively
Keywords
natural language processing; syntactic subcategorizations, parsing, learning
Abstract
Learning algorithms that acquire syntactic knowledge for a parser from sample sentences entered by users who have no knowledge of the parser or English syntax are described. It is shown how the subcategorizations of verbs, nouns and adjectives can be inferred from sample sentences entered by end users. Then, if the parser fails to parse a sentence, for example Peter knows how to read books, because it has limited knowledge or no knowledge at all about 'know', an interface which incorporates the acquisition algorithms can be activated, and 'know' can be defined by entering some sample sentences, one of which can be the one which the parser failed to parse. © 1995.
Publication Date
1-1-1995
Publication Title
Knowledge-Based Systems
Volume
8
Issue
4
Number of Pages
190-200
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/0950-7051(95)96216-E
Copyright Status
Unknown
Socpus ID
0029358257 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0029358257
STARS Citation
Gomez, Fernando, "Learning Word Syntactic Subcategorizations Interactively" (1995). Scopus Export 1990s. 1823.
https://stars.library.ucf.edu/scopus1990/1823