Paper: Combination Of Symbolic And Statistical Approaches For Grammatical Knowledge Acquisition

ACL ID A94-1012
Title Combination Of Symbolic And Statistical Approaches For Grammatical Knowledge Acquisition
Venue Applied Natural Language Processing Conference
Session Main Conference
Year 1994
Authors
  • Masaki Kiyono (University of Manchester, Manchester UK; Matsushita Electric Industrial Co. Ltd., Japan)
  • Jun'ichi Tsujii (University of Manchester, Manchester UK)

The framework we adopted for customiz- ing linguistic knowledge to individual ap- plication domains is an integration of sym- bolic and statistical approaches. In or- der to acquire domain specific knowledge, we have previously proposed a rule-based mechanism to hypothesize missing knowl- edge from partial parsing results of unsuc- cessfully parsed sentences. In this paper, we focus on the statistical process which se- lects plausible knowledge from a set of hy- potheses generated from the whole corpus. In particular, we introduce two statistical measures of hypotheses, Local Plausibility and Global Plausibility, and describe how these measures are determined iteratively. The proposed method will be incorporated into the tool kit for linguistic knowledge acquisition which we are now develo...