Robust German Noun Chunking With a Probabilistic Context-Free Grammar

We present a noun chunker for German which is based on a head-lexicalised probabilistic contextfl'ee grammar. A manually developed grammar was semi-automatically extended with robustness rules in order to allow parsing of unrestricted text. Tile model parmncters were learned from unlabellcd training data by a probabilistic context-fl'ee parser. For extracting noun chunks, the parser generates all possible noun chunk analyses, scores them with a novel algorithm which maximizes tile best chunk sequence criterion, and chooscs the most probable chunk sequence. An evaluation of the chunker on 2,140 hand-annotated noun chunks yielded 92% recall and 93% precision.

• Type: Conference
• Year: 2000
• Where: COLING
• Authors: Helmut Schmid, Sabine Schulte im Walde
• Keywords: Chunk Sequence, COLING 2000, COLING 2008, Noun Chunks, Possible Noun Chunk