Danilo Giampiccolo

The Third PASCAL Recognizing Textual Entailment Challenge

This paper presents the Third PASCAL Recognising Textual Entailment Challenge (RTE-3), providing an overview of the dataset creating methodology and the submitted systems. In creating this years dataset, a number of longer texts were introduced to make the challenge more oriented to realistic scenarios. Additionally, a pool of resources was offered so that the participants could share common tools. A pilot task was also set up, aimed at differentiating unknown entailments from identified contradictions and providing justifications for overall system decisions. 26 participants submitted 44 runs, using different approaches and generally presenting new entailment models and achieving higher scores than in the previous challenges.

Overview of ResPubliQA 2009: question answering evaluation over European legislation

This paper describes the first round of ResPubliQA, a Question Answering (QA) evaluation task over European legislation, proposed at the Cross Language Evaluation Forum (CLEF) 2009. The exercise consists of extracting a relevant paragraph of text that satisfies completely the information need expressed by a natural language question. The general goals of this exercise are (i) to study if the current QA technologies tuned for newswire collections and Wikipedia can be adapted to a new domain (law in this case); (ii) to move to a more realistic scenario, considering people close to law as users, and paragraphs as system output; (iii) to compare current QA technologies with pure Information Retrieval (IR) approaches; and (iv) to introduce in QA systems the Answer Validation technologies developed in the past three years. The paper describes the task in more detail, presenting the different types of questions, the methodology for the creation of the test sets and the new evaluation measure, and analyzing the results obtained by systems and the more successful approaches. Eleven groups participated with 28 runs. In addition, we evaluated 16 baseline runs (2 per language) based only in pure IR approach, for comparison purposes. Considering accuracy, scores were generally higher than in previous QA campaigns.