Entity Linking (EL) and Word Sense Disam-biguation (WSD) both address the lexical am-biguity of language. But while the two tasks are pretty similar, they differ in a fundamen-tal respect: in EL the textual mention can be linked to a named entity which may or may not contain the exact mention, while in WSD there is a perfect match between the word form (bet-ter, its lemma) and a suitable word sense. In this paper we present Babelfy, a unified graph-based approach to EL and WSD based on a loose identification of candidate mean-ings coupled with a densest subgraph heuris-tic which selects high-coherence semantic in-terpretations. Our experiments show state-of-the-art performances on both tasks on 6 differ-ent datasets, including a multilingua...
Entity linking, a very popular research topic nowadays, involves identi-fying mentions of ‘real worl...
We present results that show that incorporating lexical and structural semantic information is effec...
We present results that show that incorporating lexical and structural semantic information is effec...
Entity Linking (EL) and Word Sense Disam-biguation (WSD) both address the lexical am-biguity of lang...
In this paper we present the Multilingual All-Words Sense Disambiguation and Entity Link-ing task. W...
Nowadays the textual information available online is provided in an increasingly wide range of lan-g...
This paper describes the participation of the UNIBA team in the Task 13 of SemEval-2015 about Multil...
Nowadays, the human textual data constitutes a great proportion of the shared information resources ...
Semantic relatedness and disambiguation are fundamental problems for linking text documents to the ...
This paper describes a new Word Sense Disambiguation (WSD) algorithm which extends two well-known va...
Word Sense Disambiguation (WSD) can be assisted by taking advantage of the metadata embedded in the ...
Word sense disambiguation (WSD) has been a long-standing research objective for natural language pro...
We introduce a new method for unsupervised knowledge-based word sense disambiguation (WSD) based on ...
Supervised word sense disambiguation (WSD) for truly polysemous words (in contrast to homonyms) is d...
We present a hybrid knowledge-based ap-proach to multilingual word sense disam-biguation using Babel...
Entity linking, a very popular research topic nowadays, involves identi-fying mentions of ‘real worl...
We present results that show that incorporating lexical and structural semantic information is effec...
We present results that show that incorporating lexical and structural semantic information is effec...
Entity Linking (EL) and Word Sense Disam-biguation (WSD) both address the lexical am-biguity of lang...
In this paper we present the Multilingual All-Words Sense Disambiguation and Entity Link-ing task. W...
Nowadays the textual information available online is provided in an increasingly wide range of lan-g...
This paper describes the participation of the UNIBA team in the Task 13 of SemEval-2015 about Multil...
Nowadays, the human textual data constitutes a great proportion of the shared information resources ...
Semantic relatedness and disambiguation are fundamental problems for linking text documents to the ...
This paper describes a new Word Sense Disambiguation (WSD) algorithm which extends two well-known va...
Word Sense Disambiguation (WSD) can be assisted by taking advantage of the metadata embedded in the ...
Word sense disambiguation (WSD) has been a long-standing research objective for natural language pro...
We introduce a new method for unsupervised knowledge-based word sense disambiguation (WSD) based on ...
Supervised word sense disambiguation (WSD) for truly polysemous words (in contrast to homonyms) is d...
We present a hybrid knowledge-based ap-proach to multilingual word sense disam-biguation using Babel...
Entity linking, a very popular research topic nowadays, involves identi-fying mentions of ‘real worl...
We present results that show that incorporating lexical and structural semantic information is effec...
We present results that show that incorporating lexical and structural semantic information is effec...