Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
Robust probabilistic predictive syntactic processing: motivations, models, and applications
Robust probabilistic predictive syntactic processing: motivations, models, and applications
From grammar to lexicon: unsupervised learning of lexical syntax
Computational Linguistics - Special issue on using large corpora: II
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Automatic verb classification based on statistical distributions of argument structure
Computational Linguistics
Applied morphological processing of English
Natural Language Engineering
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Automatic extraction of subcategorization from corpora
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
How verb subcategorization frequencies are affected by corpus choice
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Automatic acquisition of a large subcategorization dictionary from corpora
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Comlex Syntax: building a computational lexicon
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Automatic extraction of subcategorization frames for Czech
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Clustering verbs semantically according to their alternation behaviour
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Verb class disambiguation using informative priors
Computational Linguistics
Intricacies of Collins' Parsing Model
Computational Linguistics
Parsing and disfluency placement
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
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In this paper, we compare the performance of a state-of-the-art statistical parser (Bikel, 2004) in parsing written and spoken language and in generating subcategorization cues from written and spoken language. Although Bikel's parser achieves a higher accuracy for parsing written language, it achieves a higher accuracy when extracting subcategorization cues from spoken language. Our experiments also show that current technology for extracting subcategorization frames initially designed for written texts works equally well for spoken language. Additionally, we explore the utility of punctuation in helping parsing and extraction of subcategorization cues. Our experiments show that punctuation is of little help in parsing spoken language and extracting subcategorization cues from spoken language. This indicates that there is no need to add punctuation in transcribing spoken corpora simply in order to help parsers.