Olatz Ansa

Representation and treatment of multiword expressions in Basque

This paper describes the representation of Basque Multiword Lexical Units and the automatic processing of Multiword Expressions. After discussing and stating which kind of multiword expressions we consider to be processed at the current stage of the work, we present the representation schema of the corresponding lexical units in a general-purpose lexical database. Due to its expressive power, the schema can deal not only with fixed expressions but also with morphosyntactically flexible constructions. It also allows us to lemmatize word combinations as a unit and yet to parse the components individually if necessary. Moreover, we describe HABIL, a tool for the automatic processing of these expressions, and we give some evaluation results. This work must be placed in a general framework of written Basque processing tools, which currently ranges from the tokenization and segmentation of single words up to the syntactic tagging of general texts.

Using knowledge-based relatedness for information retrieval

Traditional information retrieval (IR) systems use keywords to index and retrieve documents. The limitations of keywords were recognized since the early days, specially when different but closely related words are used in the query and the relevant document. Query expansion techniques like pseudo-relevance feedback (PRF) and document clustering techniques rely on the target document set in order to bridge the gap between those words. This paper explores the use of knowledge-based semantic relatedness techniques to overcome the vocabulary mismatch between the query and documents, both on IR and Passage Retrieval for question answering. We performed query expansion and document expansion using WordNet, with positive effects over a language modeling baseline on three datasets, and over PRF on two of those datasets. Our analysis shows that our models and PRF are complementary; in that, PRF is better for easy queries, and our models are stronger for difficult queries and that our models generalize better to other collections, being more robust to parameter adjustments. In addition, we show that our method has a positive impact in an end-to-end question answering system for Basque and that it can be readily applied to other knowledge bases, as our good results using Wikipedia show, paving the way for the use of other knowledge structures such as medical ontologies and linked data repositories.

Elhuyar-IXA: semantic relatedness and cross-lingual passage retrieval

This article describes the participation of the joint Elhuyar-IXA group in the ResPubliQA exercise at QA&CLEF. In particular, we participated in the English-English monolingual task and in the Basque-English crosslingual one. Our focus has been threefold: (1) to check to what extent information retrieval (IR) can achieve good results in passage retrieval without question analysis and answer validation, (2) to check Machine Readable Dictionary (MRD) techniques for the Basque to English retrieval when faced with the lack of parallel corpora for Basque in this domain, and (3) to check the contribution of semantic relatedness based on WordNet to expand the passages to related words. Our results show that IR provides good results in the monolingual task, that our crosslingual system performs lower than the monolingual runs, and that semantic relatedness improves the results in both tasks (by 6 and 2 points, respectively).

An XML framework for a basque question answering system

This paper presents a general platform for a Basque monolingual question answering (QA) system. It focuses on the architecture of the platform, paying special attention to: 1) the integration of the development and evaluation environments, and 2) the systematic use of XML declarative files to control the execution of the modules and the communication between them. Moreover, a first pilot experiment is discussed.