Analyzing English Syntax with a Pattern-Learning Parser

A dependency analysis system based on pattern
recognition and learning logic was developed 
to infer word classes and rules of syntactic combination
from experience with text which had been analyzed. 
 The characteristics used to form word classes are the
depth in the dependency tree of each word, the 
direction of its governor and the same features for
each of its immediate neighbors. Syntactic rules 
of combination show the relation of a word to its governor
in the depth pattern of the sentence.  The 
system was tested on 400 elementary basic English sentences
including 300 used earlier by Knowlton in 
a different learning parser of all 400 sentences.  After
experience with 300 sentences it was able to 
generalize with 77 percent accuracy to the next 100.
 In accumulative learning trials after the first 
200 sentences it averaged a probability of .9 for accurately
parsing each new sentence it encountered. 
 It was concluded that the system is adequate for learning
to parse the bulk of basic English but that 
further development is required before conclusions about
its application to ordinary English can be stored. 
 The system is operational and available on
the ARPA/SDC time-shared computing system.

CACM November, 1965

McConlogue, K.
Simmons, R. F.

CA651111 JB March 6, 1978  4:45 PM

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