Interactive theory revision: an inductive logic programming approach
Interactive theory revision: an inductive logic programming approach
Algorithmic Program DeBugging
Computational Linguistics
Three generative, lexicalised models for statistical parsing
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Some chart-based techniques for parsing ill-formed input
ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
Estimation of stochastic attribute-value grammars using an informative sample
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
EBL: an approach to automatic lexical acquisition
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 4
Learning to parse database queries using inductive logic programming
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
An introduction to inductive logic programming and learning language in logic
Learning language in logic
Experiments in inductive chart parsing
Learning language in logic
Issues in Learning Language in Logic
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part II
Towards Machine Learning of Grammars and Compilers of Programming Languages
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
A Dynamic Approach for Automatic Error Detection in Generation Grammars
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Acquisition of unknown word paradigms for large-scale grammars
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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We report work on effectively incorporating linguistic knowledge into grammar induction. We use a highly interactive bottom-up inductive logic programming (ILP) algorithm to learn 'missing' grammar rules from an incomplete grammar. Using linguistic constraints on, for example, head features and gap threading, reduces the search space to such an extent that, in the small-scale experiments reported here, we can generate and store all candidate grammar rules together with information about their coverage and linguistic properties. This allows an appealingly simple and controlled method for generating linguistically plausible grammar rules. Starting from a base of highly specific rules, we apply least general generalisation and inverse resolution to generate more general rules. Induced rules are ordered, for example by coverage, for easy inspection by the user and at any point, the user can commit to a hypothesised rule and add it to the grammar. Related work in ILP and computational linguistics is discussed.