Targeting Chinese Nominal Compounds in Corpora

For compounding languages, a great part of the topical semantics is conveyed via nominal compounds. Various applications of natural language processing can profit from explicit access to these compounds, provided by a lexicon. The best way to acquire such a resource is to harvest corpora that represent the domain in question. For Chinese, a significant difficulty arises because the text comes as a string of characters, segmented only by sentence boundaries. Extraction algorithms that solely rely on context variety do not perform precisely enough. We propose a pipeline of filters that starts from a candidate set established by accessor variety and then employs several methods to improve precision.

• Type: Conference
• Year: 2008
• Where: LREC
• Authors: Weiruo Qu, Christoph Ringlstetter, Randy Goebel
• Keywords: Education, LREC 2008, Natural Language Processing, Nominal Compounds, Significant Difficulty Arises