Selecting Answers with Structured Lexical Expansion and Discourse Relations LIMSI's Participation at QA4MRE 2013
نویسندگان
چکیده
In this paper, we present the LIMSI’s participation to QA4MRE 2013.We decided to test two kinds of methods. The first one focuses on complex questions, such as causal questions, and exploits discourse relations. Relation recognition shows promising results, however it has to be improved to have an impact on answer selection. The second method is based on semantic variations. We explored the English Wiktionary to find reformulations of words in the definitions, and used these reformulations to index the documents and select passages in the Entrance exams task.
منابع مشابه
Adaptation of LIMSI's QALC for QA4MRE
In this paper, we present LIMSI participation to one of the pilot tasks of QA4MRE at CLEF 2012: Machine Reading of Biomedical Texts about Alzheimer. For this exercise, we adapted an existing question answering (QA) system, QALC, by searching answers in the reading document. This basic version was used for the evaluation and obtains 0.2, which was increased to 0.325 after basic corrections. We d...
متن کاملQuestion Answering System Using Query Expansion and Heuristic Features
This paper describes the design of question answering system that participates in the maintask of QA4MRE at CLEF 2013. This system will initially perform preprocessing stage of the document and the documents related questions. Then, it identifies the type of questions in order to be able to search the answers with the most appropriate approach. In order to finding the answers, the system uses e...
متن کاملTesting Lexical Approaches in QA4MRE
In this paper we describe our strategy in the course of our participation in the 2012 QA4MRE main task. We follow a lexical approach, based on both Word Proximity and similarity measures. In the former, we implement a method that was successfully applied in the “Who Wants to be a Millionaire” contest; in the later we use the notion of “extent”, that is, a passage that includes terms of the give...
متن کاملCombining Text Mining Techniques for QA4MRE 2013
This paper describes a lexical system developed for the main task of Question Answering for Machine Reading Evaluation 2013 (QA4MRE). The presented system executes the preprocessing of test documents, and generates hypotheses consisting of the question text combined with text from possible answers for the question. The hypotheses are compared to sentences from the text by the means of a set sim...
متن کاملLIMSI's participation to the 2013 shared task on Native Language Identification
This paper describes LIMSI’s participation to the first shared task on Native Language Identification. Our submission uses a Maximum Entropy classifier, using as features character and chunk n-grams, spelling and grammatical mistakes, and lexical preferences. Performance was slightly improved by using a twostep classifier to better distinguish otherwise easily confused native languages.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013