Paper: Parsing Noun Phrase Structure with CCG

ACL ID P08-1039
Title Parsing Noun Phrase Structure with CCG
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008

Statistical parsing of noun phrase (NP) struc- ture has been hampered by a lack of gold- standard data. This is a significant problem for CCGbank, where binary branching NP deriva- tions are often incorrect, a result of the auto- matic conversion from the Penn Treebank. We correct these errors in CCGbank using a gold-standard corpus of NP structure, result- ing in a much more accurate corpus. We also implement novel NER features that generalise the lexical information needed to parse NPs and provide important semantic information. Finally, evaluating against DepBank demon- strates the effectiveness of our modified cor- pus and novel features, with an increase in parser performance of 1.51%.