Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Towards a theory of natural language interfaces to databases
Proceedings of the 8th international conference on Intelligent user interfaces
Automatic labeling of semantic roles
Computational Linguistics
Text classification using string kernels
The Journal of Machine Learning Research
Intricacies of Collins' Parsing Model
Computational Linguistics
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
A statistical semantic parser that integrates syntax and semantics
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Learning to parse database queries using inductive logic programming
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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
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
Learning information intent via observation
Proceedings of the 16th international conference on World Wide Web
Composing Questions through Conceptual Authoring
Computational Linguistics
Discriminative reranking for semantic parsing
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Semantic parsing with structured SVM ensemble classification models
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Supporting Named Entity Recognition and Syntactic Analysis with Full-Text Queries
NLDB '08 Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems
Mining Natural Language Programming Directives with Class-Oriented Bayesian Networks
ADMA '08 Proceedings of the 4th international conference on Advanced Data Mining and Applications
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
Transforming meaning representation grammars to improve semantic parsing
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
A unified knowledge based approach for sense disambiguationm and semantic role labeling
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
A dependency-based word subsequence kernel
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A generative model for parsing natural language to meaning representations
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Semi-supervised learning for semantic parsing using support vector machines
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
Learning language semantics from ambiguous supervision
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Natural language generation with tree conditional random fields
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Generic querying of relational databases using natural language generation techniques
INLG '06 Proceedings of the Fourth International Natural Language Generation Conference
A statistical semantic parser that integrates syntax and semantics
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Inducing probabilistic CCG grammars from logical form with higher-order unification
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Learning dependency-based compositional semantics
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
A maximum entropy model for transforming sentences to logical form
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
NLP (natural language processing) for NLP (natural language programming)
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
Lexical generalization in CCG grammar induction for semantic parsing
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A semi supervised learning model for mapping sentences to logical form with ambiguous supervision
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
Parsing time: learning to interpret time expressions
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
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
SmartSynth: synthesizing smartphone automation scripts from natural language
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
Learning dependency-based compositional semantics
Computational Linguistics
Efficient latent structural perceptron with hybrid trees for semantic parsing
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
| Hi-index | 0.00 |
This paper presents a method for inducing transformation rules that map natural-language sentences into a formal query or command language. The approach assumes a formal grammar for the target representation language and learns transformation rules that exploit the non-terminal symbols in this grammar. The learned transformation rules incrementally map a natural-language sentence or its syntactic parse tree into a parse-tree for the target formal language. Experimental results are presented for two corpora. one which maps English instructions into an existing formal coaching language for simulated RoboCup soccer agents, and another which maps English U.S.-geography questions into a database query language. We show that our method performs overall better and faster than previous approaches in both domains.