Improvements in Unsupervised Co-Occurrence Based Parsing
Christian Hänig · 2010
This paper presents an algorithm for unsupervised co-occurrence based parsing that improves and extends existing approaches. The proposed algorithm induces a contextfree grammar of the language in question in an iterative manner. The resulting structure of a sentence will be given as a hierarchical arrangement of constituents. Although 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 composition possibilities. For evaluation purposes, 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. 1