Generating an entailment corpus from news headlines
EMSEE '05 Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment
Evaluating semantic evaluations: how RTE measures up
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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The MiTAP system was developed as an experimental prototype using human language technologies for monitoring disease outbreaks. The system provides timely, multi-lingual, global information access to analysts, medical experts and individuals involved in humanitarian assistance. Thousands of articles from electronic information sources spanning multiple languages are automatically captured, translated, tagged, summarized, and presented to users in a variety of ways. Real users access MiTAP daily to solve real problems. The successful adoption of MiTAP is attributed to its user-focused design that accommodates the imperfect component technologies and allows users to interact with the system in familiar ways. We will discuss the problem, design process, and implementation from the perspective of services provided and how these services support system capabilities that satisfy user requirements.