A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
PRINCIPAR: an efficient, broad-coverage, principle-based parser
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Finding parts in very large corpora
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Using knowledge to facilitate factoid answer pinpointing
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Learning surface text patterns for a Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Learning semantic constraints for the automatic discovery of part-whole relations
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Offline strategies for online question answering: answering questions before they are asked
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
Inducing ontological co-occurrence vectors
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Espresso: leveraging generic patterns for automatically harvesting semantic relations
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
WhyNot: debugging failed queries in large knowledge bases
IAAI'02 Proceedings of the 14th conference on Innovative applications of artificial intelligence - Volume 1
The Future of Text-Meaning in Computational Linguistics
TSD '08 Proceedings of the 11th international conference on Text, Speech and Dialogue
Learning by reading: a prototype system, performance baseline and lessons learned
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
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It has long been a dream to build computer systems that learn automatically by reading text This dream is generally considered infeasible, but some surprising developments in the US over the past three years have led to the funding of several short-term investigations into whether and how much the best current practices in Natural Language Processing and Knowledge Representation and Reasoning, when combined, actually enable this dream This paper very briefly describes one of these efforts, the Learning by Reading project at ISI, which has converted a high school textbook of Chemistry into very shallow logical form and is investigating which semantic features can plausibly be added to support the kinds of inference required for answering standard high school text questions.