Paper: Improvements in Unsupervised Co-Occurrence Based Parsing

ACL ID W10-2901
Title Improvements in Unsupervised Co-Occurrence Based Parsing
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2010

This paper presents an algorithm for unsu- pervised co-occurrence based parsing that improves and extends existing approaches. The proposed algorithm induces a context- free grammar of the language in question in an iterative manner. The resulting struc- ture of a sentence will be given as a hier- archical arrangement of constituents. Al- though this algorithm does not use any a priori knowledge about the language, it is able to detect heads, modifiers and a phrase type’s different compound compo- sition possibilities. For evaluation pur- poses, the algorithm is applied to manually annotated part-of-speech tags (POS tags) as well as to word classes induced by an unsupervised part-of-speech tagger.