Inductive Logic Programming

Information extraction systems process natural language documents and locate a specific set of relevant items. Given the recent success of empirical or corpus- based approaches in other areas of natu- …...

We report work on effectively incorporating lin- guistic knowledge into grammar induction. We use a highly interactive bottom-up inductive logic programming (ILP) algorithm to learn 'missing' grammar rules from an …...

In this paper, we propose an Inductive Logic Programming learning method which aims at automatically extracting special Noun-Verb (N- V) pairs from a corpus in order to build up semantic …...

. This paper presents and evaluates an original approach to automatically align bitexts at the word level. It relies on a syntactic dependency analysis of the texts and uses a …...

We present a novel approach to the word sense disambiguation problem which makes use of corpus-based evidence com- bined with background knowledge. Em- ploying an inductive logic programming algorithm, the …...

We describe two systems participating of the English Lexical Sample task in SemEval- 2007. The systems make use of Inductive Logic Programming for supervised learning in two different ways: (a) …...

The traditional mention-pair model for coref- erence resolution cannot capture information beyond mention pairs for both learning and testing. To deal with this problem, we present an expressive entity-mention model …...

AbstractThis paper presents and evaluates an original approach to automatically align bitexts at the word level. It relies on a syntactic dependency analysis of the source and target texts and …...

AbstractThe recent success of natural language understanding (NLU) systems has been troubled by results highlighting the failure of these models to generalize in a systematic and robust way. In this …...