Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
In question answering, two heads are better than one
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
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
An empirical comparison of supervised learning algorithms
ICML '06 Proceedings of the 23rd international conference on Machine learning
Using string-kernels for learning semantic parsers
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Effective self-training for parsing
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Learning for semantic parsing with statistical machine translation
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Word-Level Confidence Estimation for Machine Translation
Computational Linguistics
Semantic parsing with structured SVM ensemble classification models
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Learning to sportscast: a test of grounded language acquisition
Proceedings of the 25th international conference on Machine learning
Computing confidence scores for all sub parse trees
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Detecting parser errors using web-based semantic filters
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Confidence estimation for information extraction
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
Unsupervised constraint driven learning for transliteration discovery
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Reinforcement learning for mapping instructions to actions
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Learning semantic correspondences with less supervision
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Learning context-dependent mappings from sentences to logical form
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
A statistical semantic parser that integrates syntax and semantics
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Bootstrapping semantic analyzers from non-contradictory texts
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Learning to parse database queries using inductive logic programming
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Driving semantic parsing from the world's response
CoNLL '10 Proceedings of the Fourteenth Conference on Computational Natural Language Learning
Improved unsupervised POS induction using intrinsic clustering quality and a Zipfian constraint
CoNLL '10 Proceedings of the Fourteenth Conference on Computational Natural Language Learning
A Bayesian model for unsupervised semantic parsing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
A Bayesian model for unsupervised semantic parsing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Bootstrapping semantic parsers from conversations
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Lexical generalization in CCG grammar induction for semantic parsing
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A Bayesian approach to unsupervised semantic role induction
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Learning to win by reading manuals in a monte-carlo framework
Journal of Artificial Intelligence Research
Fast online lexicon learning for grounded language acquisition
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Crosslingual induction of semantic roles
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Weakly supervised training of semantic parsers
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Learning dependency-based compositional semantics
Computational Linguistics
ReliAble dependency arc recognition
Expert Systems with Applications: An International Journal
Introduction to the special issue on learning semantics
Machine Learning
Learning from natural instructions
Machine Learning
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Current approaches for semantic parsing take a supervised approach requiring a considerable amount of training data which is expensive and difficult to obtain. This supervision bottleneck is one of the major difficulties in scaling up semantic parsing. We argue that a semantic parser can be trained effectively without annotated data, and introduce an unsupervised learning algorithm. The algorithm takes a self training approach driven by confidence estimation. Evaluated over Geoquery, a standard dataset for this task, our system achieved 66% accuracy, compared to 80% of its fully supervised counterpart, demonstrating the promise of unsupervised approaches for this task.