AQAa multilingual anaphora annotation scheme for question answering

1. Boldrini, Ester
2. Puchol Blasco, Marcel
3. Navarro, B.
4. Martínez Barco, Patricio
5. Vargas Sierra, Chelo

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More publications in: Procesamiento del lenguaje natural

Abstract

This paper presents AQA, a multilingual anaphora annotation scheme that can be applied in Machine Learning for the improvement of Question Answering systems. It has been used to annotate the collection of CLEF 2008 in Spanish, Italian and English. AQA is inspired by the MATE meta-model, which has been adjusted to our needs. By using AQA we specify the relationship between the anaphora and its antecedent, cases of topic and subtopic, and we label different types of anaphoric expressions. A blind annotation was carried out by two annotators, and a referee for solving cases of disagreement. The results of the evaluation show an 87% level of inter-annotator agreement. Some annotation problems will be reported in this paper. Our aim is to extend this model to other languages, and to apply it to the development of an Anaphora Resolution system based on Machine Learning techniques in order to improve a real human machine-interaction.

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