Andrew Hazen Schlaikjer

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In recent years, question answering (QA) systems such as those in the yearly TREC conferences have reached a remarkably high level of performance. These systems are premised on the short-answer model, in which the goal is to answer questions for which the correct response is a number, short phrase, or sentence fragment. However, many questions that occur in(More)
In this paper we describe question answering research being pursued as a joint project between Columbia University and the University of Colorado at Boulder as part of ARDA's AQUAINT program. As a foundation for targeting complex questions involving opinions, events, and paragraph-length answers, we recently built two systems for answering short factual(More)
We present an overview of DefScriber, a system developed at Columbia University that combines knowledge-based and statistical methods to answer definitional questions of the form, " What is X? " We discuss how DefScriber was applied to the definition questions in the TREC 2003 QA track main task. We conclude with an analysis of our system's results on the(More)
We present DefScriber, a fully implemented system that combines knowledge-based and statistical methods in forming multi-sentence answers to open-ended defi-nitional questions of the form, " What is X? " We show how a set of definitional predicates proposed as the knowledge-based side of our approach can be used to guide the selection of definitional(More)
In this paper, we describe the JAVELIN Cross Language Question Answering system, which includes modules for question analysis, keyword translation, document retrieval, information extraction and answer generation. In the NTCIR6 CLQA2 evaluation, our system achieved 19% and 13% accuracy in the English-to-Chinese and English-to-Japanese subtasks,(More)
Current question answering tasks handle definitional questions by seeking answers which are factual in nature. While factual answers are a very important component in defining entities, a wealth of qualitative data is often ignored. In this incipient work, we define qualitative dimensions (credibility, sentiment, contradictions etc.) for evaluating answers(More)