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SemEval 2018 Task 2: Multilingual Emoji Prediction
Comunicacio presentada al 12th International Workshop on Semantic Evaluation (SemEval-2018), celebrat els dies 5 i 6 de juny de 2018 a Nova Orleans, EUA.
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SemEval-2018 Task 9: Hypernym Discovery
Comunicacio presentada al 12th International Workshop on Semantic Evaluation (SemEval-2018), celebrat els dies 5 i 6 de juny de 2018 a Nova Orleans, EUA.
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Information extraction for knowledge base construction in the music domain
The rate at which information about music is being created and shared on the web is growing exponentially. However, the challenge of making sense of all this data remains an open problem. In thisExpand
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ExTaSem! Extending, Taxonomizing and Semantifying Domain Terminologies
We introduce EXTASEM!, a novel approach for the automatic learning of lexical taxonomies from domain terminologies. First, we exploit a very large semantic network to collect thousands of in-domainExpand
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Interpretable Emoji Prediction via Label-Wise Attention LSTMs
Human language has evolved towards newer forms of communication such as social media, where emojis (i.e., ideograms bearing a visual meaning) play a key role. While there is an increasing body ofExpand
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Syntactically Aware Neural Architectures for Definition Extraction
Automatically identifying definitional knowledge in text corpora (Definition Extraction or DE) is an important task with direct applications in, among others, Automatic Glossary Generation, TaxonomyExpand
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Supervised Distributional Hypernym Discovery via Domain Adaptation
Comunicacio presentada a la Conference on Empirical Methods in Natural Language Processing celebrada els dies 1 a 5 de novembre de 2016 a Austin, Texas.
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Improving Cross-Lingual Word Embeddings by Meeting in the Middle
Cross-lingual word embeddings are becoming increasingly important in multilingual NLP. Recently, it has been shown that these embeddings can be effectively learned by aligning two disjointExpand
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Semantics-Driven Recognition of Collocations Using Word Embeddings
L2 learners often produce “ungrammatical” word combinations such as, e.g., *give a suggestion or *make a walk. This is because of the “collocationality” of one of their items (the base) that limitsExpand
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Knowledge Base Unification via Sense Embeddings and Disambiguation
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 consistsExpand
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