Deep Read: a reading comprehension system
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Using grammatical relations to compare parsers
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Entailment and anaphora resolution in RTE3
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
VENSES – a linguistically-based system for semantic evaluation
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
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Summarization and Question Answering need precise linguistic information with a much higher coverage than what is being offered by currently available statistically based systems. We assume that the starting point of any interesting application in these fields must necessarily be a good syntacticsemantic parser. In this paper we present the system for text understanding called GETARUNS, General Text and Reference Understanding System (Delmonte, 2003a). The heart of the system is a rule-based top-down DCG-style parser, which uses an LFG oriented grammar organization. The parser produces an f-structure as a DAG which is then used to create a Logical Form, the basis for all further semantic representation. GETARUNS, has a highly sophisticated linguistically based semantic module which is used to build up the Discourse Model. Semantic processing is strongly modularized and distributed amongst a number of different submodules which take care of Spatio-Temporal Reasoning, Discourse Level Anaphora Resolution.