Flat noun phrase structure was, up until recently, the standard in annotation for the Penn Treebanks. With the recent addition of internal noun phrase annotation, dependency parsing and applications down the NLP pipeline are likely affected. Some machine translation systems, such as TectoMT, use deep syntax as a language transfer layer. It is proposed that changes to the noun phrase dependency parse will have a cascading effect down the NLP pipeline and in the end, improve machine translation output, even with a reduction in parser accuracy that the noun phrase structure might cause. This paper examines this noun phrase structure's effect on dependency parsing, in English, with a maximum spanning tree parser and shows a 2.43%, 0.23 Bleu score, improvement for English to Czech machine translation.
REF explored the effects of noun phrase bracketing in dependency parsing in English, and further on English to Czech machine translation. But the work focused on using noun phrase structure to improve a machine translation framework.
Effects of Noun Phrase Bracketing in Dependency Parsing and Machine Translation
Proceedings of the ACL 2011 Student Session
Computer Science