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Lexical taxonomies are graph-like hierarchical structures that provide a formal representation of knowledge. Most knowledge graphs to date rely on is-a (hypernymic) relations as the backbone of their semantic structure. In this paper, we propose a supervised distributional framework for hypernym discovery which operates at the sense level, enabling(More)
We present DEFIE, an approach to large-scale Information Extraction (IE) based on a syntactic-semantic analysis of textual definitions. Given a large corpus of definitions we leverage syntactic dependencies to reduce data sparsity, then disambiguate the arguments and content words of the relation strings, and finally exploit the resulting information to(More)
We present KB-UNIFY, a novel approach for integrating the output of different Open Information Extraction systems into a single unified and fully disambiguated knowledge repository. KB-UNIFY consists of three main steps: (1) disambigua-tion of relation argument pairs via a sense-based vector representation and a large unified sense inventory; (2) ranking of(More)
The hyperlink structure of Wikipedia constitutes a key resource for many Natural Language Processing tasks and applications, as it provides several million semantic annotations of entities in context. Yet only a small fraction of mentions across the entire Wikipedia corpus is linked. In this paper we present the automatic construction and evaluation of a(More)
Linking concepts and named entities to knowledge bases has become a crucial Natural Language Understanding task. In this respect, recent works have shown the key advantage of exploiting textual definitions in various Natural Language Processing applications. However, to date there are no reliable large-scale corpora of sense-annotated textual definitions(More)
Definition Extraction is the task to identify snippets of free text in which a term is defined. While lexicographic studies have proposed different definition typologies and categories, most NLP tasks aimed at revealing word or concept meanings have traditionally dealt with lexicographic (encyclopedic) definitions, for example, as a prior step to ontology(More)
This paper describes SEW-EMBED, our language-independent approach to multilingual and cross-lingual semantic word similarity as part of the SemEval-2017 Task 2. We leverage the Wikipediabased concept representations developed by Raganato et al. (2016), and propose an embedded augmentation of their explicit high-dimensional vectors, which we obtain by(More)
Parallel corpora are widely used in a variety of Natural Language Processing tasks, from Machine Translation to cross-lingual Word Sense Disambiguation, where parallel sentences can be exploited to automatically generate high-quality sense annotations on a large scale. In this paper we present EUROSENSE, a multilingual sense-annotated resource based on the(More)
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