Automatic Partial Parsing Rule Acquisition Using Decision Tree Induction

Abstract. Partial parsing techniques try to recover syntactic information efficiently and reliably by sacrificing completeness and depth of analysis. One of the difficulties of partial parsing is finding a means to extract the grammar involved automatically. In this paper, we present a method for automatically extracting partial parsing rules from a tree-annotated corpus using decision tree induction. We define the partial parsing rules as those that can decide the structure of a substring in an input sentence deterministically. This decision can be considered as a classification; as such, for a substring in an input sentence, a proper structure is chosen among the structures occurred in the corpus. For the classification, we use decision tree induction, and induce partial parsing rules from the decision tree. The acquired grammar is similar to a phrase structure grammar, with contextual and lexical information, but it allows building structures of depth one or more. Our experimen...

• Type: Conference
• Year: 2005
• Where: IJCNLP
• Authors: Myung-Seok Choi, Chul Su Lim, Key-Sun Choi
• Keywords: Decision Tree Induction, IJCNLP 2005, Natural Language Processing, Partial Parsing, Partial Parsing Rules