Type

Conference Proceedings

Authors

Josef van Genabith
Jennifer Foster

Subjects

Linguistics

Topics
self training state of the art parsers parser evaluation machine translating evaluation metrics english parser

Parser evaluation and the BNC: evaluating 4 constituency parsers with 3 metrics (2008)

Abstract We evaluate discriminative parse reranking and parser self-training on a new English test set using four versions of the Charniak parser and a variety of parser evaluation metrics. The new test set consists of 1,000 hand-corrected British National Corpus parse trees. We directly evaluate parser output using both the Parseval and the Leaf Ancestor metrics. We also convert the hand-corrected and parser output phrase structure trees to dependency trees using a state-of-the-art functional tag labeller and constituent-to-dependency conversion tool, and then calculate label accuracy, unlabelled attachment and labelled attachment scores over the dependency structures. We find that reranking leads to a performance improvement on the new test set (albeit a modest one). We find that self-training using BNC data leads to significantly better results. However, it is not clear how effective self-training is when the training material comes from the North American News Corpus.
Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> Subject = Computer Science
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: National Centre for Language Technology (NCLT)
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres

Full list of authors on original publication

Josef van Genabith, Jennifer Foster

Experts in our system

1
Jennifer Foster
Dublin City University
Total Publications: 53