A maximum entropy approach to natural language processing
Computational Linguistics
Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Forgetting Exceptions is Harmful in Language Learning
Machine Learning - Special issue on natural language learning
Learning to Parse Natural Language with Maximum Entropy Models
Machine Learning - Special issue on natural language learning
The syntactic process
Maximum entropy models for natural language ambiguity resolution
Maximum entropy models for natural language ambiguity resolution
Improving accuracy in word class tagging through the combination of machine learning systems
Computational Linguistics
TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Estimators for stochastic "Unification-Based" grammars
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Sequential conditional Generalized Iterative Scaling
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Chunking with maximum entropy models
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Enriching the knowledge sources used in a maximum entropy part-of-speech tagger
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
A comparison of algorithms for maximum entropy parameter estimation
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Sequence modelling for sentence classification in a legal summarisation system
Proceedings of the 2005 ACM symposium on Applied computing
Deep syntactic processing by combining shallow methods
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Bootstrapping POS taggers using unlabelled data
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Language independent NER using a maximum entropy tagger
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Blueprint for a high performance NLP infrastructure
SEALTS '03 Proceedings of the HLT-NAACL 2003 workshop on Software engineering and architecture of language technology systems - Volume 8
Log-linear models for wide-coverage CCG parsing
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Parsing the WSJ using CCG and log-linear models
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Supersense tagging of unknown nouns using semantic similarity
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Multi-tagging for lexicalized-grammar parsing
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
The importance of supertagging for wide-coverage CCG parsing
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Extractive summarisation of legal texts
Artificial Intelligence and Law - AI & law in eGovernment and eDemocracy part I
Linguistically motivated large-scale NLP with C&C and boxer
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Bootstrapping and evaluating named entity recognition in the biomedical domain
BioNLP '06 Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis
Extremely lexicalized models for accurate and fast HPSG parsing
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Improving the efficiency of a wide-coverage CCG parser
IWPT '07 Proceedings of the 10th International Conference on Parsing Technologies
Porting a lexicalized-grammar parser to the biomedical domain
Journal of Biomedical Informatics
Bootstrapping and evaluating named entity recognition in the biomedical domain
LNLBioNLP '06 Proceedings of the HLT-NAACL BioNLP Workshop on Linking Natural Language and Biology
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Accurate argumentative zoning with maximum entropy models
NLPIR4DL '09 Proceedings of the 2009 Workshop on Text and Citation Analysis for Scholarly Digital Libraries
Named entity recognition in Wikipedia
People's Web '09 Proceedings of the 2009 Workshop on The People's Web Meets NLP: Collaboratively Constructed Semantic Resources
Searching for ground truth: a stepping stone in automating genre classification
DELOS'07 Proceedings of the 1st international conference on Digital libraries: research and development
Edinburgh-LTG: TempEval-2 system description
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
Chart pruning for fast lexicalised-grammar parsing
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Datasets for generic relation extraction*
Natural Language Engineering
Cross-lingual question answering using off-the-shelf machine translation
CLEF'04 Proceedings of the 5th conference on Cross-Language Evaluation Forum: multilingual Information Access for Text, Speech and Images
The challenges of parsing Chinese with combinatory categorial grammar
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
A sequence labelling approach to quote attribution
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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This paper investigates two elements of Maximum Entropy tagging: the use of a correction feature in the Generalised Iterative Scaling (GIS) estimation algorithm, and techniques for model smoothing. We show analytically and empirically that the correction feature, assumed to be required for the correctness of GIS, is unnecessary. We also explore the use of a Gaussian prior and a simple cutoff for smoothing. The experiments are performed with two tagsets: the standard Penn Treebank POS tagset and the larger set of lexical types from Combinatory Categorial Grammar.