Mining Knowledge fromWikipedia for the Question Answering task

By Davide Buscaldi, Paolo Rosso. 2006

72 citations recorded by the source corpus.

Although significant advances have been made recently in the Question Answering technology, more steps have to be undertaken in order to obtain better results. Moreover, the best systems at the CLEF and TREC evaluation exercises are very complex systems based on custom-built, expensive ontologies whose aim is to provide the systems with encyclopedic knowledge. In this paper we investigated the use of Wikipedia, the open domain encyclopedia, for the Question Answering task. Previous works considered Wikipedia as a resource where to look for the answers to the questions. We focused on some different aspects of the problem, such as the validation of the answers as returned by our Question Answering System and on the use of Wikipedia “categories” in order to determine a set of patterns that should fit with the expected answer. Validation consists in, given a possible answer, saying wether it is the right one or not. The possibility to exploit the categories ofWikipedia was not considered until now. We performed our experiments using the Spanish version of Wikipedia, with the set of questions of the last CLEF Spanish monolingual exercise. Results show that Wikipedia is a potentially useful resource for the Question Answering task.

Subfields: Artificial Intelligence, Information Retrieval & Search, Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jason Aaron Edward Weston
2. Danqi Chen
3. Mohit Bansal
4. Luke S. Zettlemoyer
5. Hannaneh Hajishirzi
6. Antoine Bordes
7. Christopher D. Manning
8. Percy Liang

In Information Retrieval & Search

1. Jason Aaron Edward Weston
2. Danqi Chen
3. Antoine Bordes
4. Carlos Gómez-Rodríguez
5. David Vilares
6. Hannaneh Hajishirzi
7. Adam Fisch
8. Wen-tau Yih

In Natural Language Processing

1. Jason Aaron Edward Weston
2. Danqi Chen
3. Mohit Bansal
4. Antoine Bordes
5. Hannaneh Hajishirzi
6. Christopher D. Manning
7. Luke S. Zettlemoyer
8. Jianfeng Gao

Citations in the corpus

• Reading Wikipedia to Answer Open-Domain Questions (2017, background): “Buscaldi and Rosso (2006) also mine knowledge from Wikipedia for QA.”
• Open domain question answering using Wikipedia-based knowledge model (2014, methodology): “Furthermore, Wikipedia was applied to QA systems as a knowledge base (Ahn et al., 2004; Buscaldi & Rosso, 2006; Simmons, 2012).”
• HEAD-QA: A Healthcare Dataset for Complex Reasoning (2019, background): “Although some research on Spanish QA has been done in the last decade (Magnini et al., 2003; Vicedo et al., 2003; Buscaldi and Rosso, 2006; Kamateri et al., 2019), most recent work has been done for English, in part due to the larger availability of resources.”