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Systems for inducing concept descriptions from examples are valuable tools for assisting in the task of knowledge acquisition for expert systems. This paper presents a description and empirical evaluation of a new induction system, cn2, designed for the ecient induction of simple, comprehensible production rules in domains where problems of poor description(More)
Our goal is to extract answers from pre-retrieved sentences for Question Answering (QA). We construct a linear-chain Conditional Random Field based on pairs of questions and their possible answer sentences, learning the association between questions and answer types. This casts answer extraction as an answer sequence tagging problem for the first time,(More)
Building a knowledge base for a given domain traditionally involves a subject matter expert and a knowledge engineer. One of the goals of our research is to eliminate the knowledge engineer. There are at least two ways to achieve this goal: train domain experts to write axioms (<i>i.e.</i>, turn them into knowledge engineers) or create tools that allow(More)
This paper presents the Seventh Recognizing Textual Entailment (RTE-7) challenge. This year's challenge replicated the exercise proposed in RTE-6, consisting of a Main Task, in which Textual Entailment is performed on a real corpus in the Update Summarization scenario; a Main subtask aimed at detecting novel information; and a KBP Validation Task, in which(More)
Grid users may wish to have fine-grained control of quality of service (QoS) guarantees in a network in order to allow timely data transfer in a distributed application environment. We present a discussion of the issues and problems involved, with some critical analysis. We propose possible solutions by making reference to and analysing existing work. Also,(More)
This paper examines the induction of classification rules from examples using real-world data. Real-world data is almost always characterized by two features, which are important for the design of an induction algorithm. Firstly, there is often noise present, for example, due to imperfect measuring equipment used to collect the data. Secondly the(More)
We present the results of the Joint Student Response Analysis and 8th Recognizing Tex-tual Entailment Challenge, aiming to bring together researchers in educational NLP technology and textual entailment. The task of giving feedback on student answers requires semantic inference and therefore is related to recognizing textual entailment. Thus, we offered to(More)
In this paper, we describe an investigation into the reuse and application of an existing ontology for the purpose of specifying and formally developing software for aircraft design. Our goals were to clearly identify the processes involved in the task, and assess the cost-effectiveness of reuse. Our conclusions are that (re)using an ontology is far from an(More)