This paper accounts for Priberam's participation in the monolingual question answering (QA) track of CLEF 2007. In previous participations, Priberam’s QA system obtained en...
Most previous corpus-based algorithms disambiguate a word with a classifier trained from previous usages of the same word. Separate classifiers have to be trained for different wo...
Question Answering (QA) is a task that deserves more collaboration between Natural Language Processing (NLP) and Knowledge Representation (KR) communities, not only to introduce r...
Porting a Natural Language Processing (NLP) system to a new domain remains one of the bottlenecks in syntactic parsing, because of the amount of effort required to fix gaps in the...
We present a syntactically enriched vector model that supports the computation of contextualized semantic representations in a quasi compositional fashion. It employs a systematic...