Синтаксические зависимости

This paper proposes a novel method to analyze syntactic dependencies and label semantic dependencies around both the verbal predicates and the nouns. In this method, a probabilistic model is designed …...

The Conference on Computational Natu- ral Language Learning is accompanied ev- ery year by a shared task whose purpose is to promote natural language processing applications and evaluate them in …...

We propose a system which builds, in a semi-supervised manner, a resource that aims at helping a NER system to anno- tate corpus-specific named entities. This system is based on …...

Bilingual Lexicon Extraction from Comparable Corpora by Combining Contextual Repre- sentations Word’s context characterisation constitute the heart of most methods of bilingual lexicon extraction from comparable corpora. In this article, …...

AbstractWe present the components of a processing chain for the creation, visualization, and validation of lexical resources (formed of terms and relations between terms). The core of the chain is …...

AbstractUnsupervised word classes induced from unannotated text corpora are increasingly used to help tasks addressed by supervised classification, such as standard named entity detection. This paper studies the contribution of …...

AbstractWe 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 …...

This paper describes in detail the approach carried out by the GTI research group for Se- mEval 2016 Task 5: Aspect-Based Sentiment Analysis, for the different subtasks proposed, as well …...

AbstractText analysis methods widely used in digital humanities often involve word co-occurrence, e.g. concept co-occurrence networks. These methods provide a useful corpus overview, but cannot determine the predicates that relate …...

This paper presents a two-step procedure to extract positive meaning from verbal negation. We first generate potential positive interpre- tations manipulating syntactic dependencies. Then, we score them according to their …...

AbstractWe present a linguistic analysis of a set of English and Spanish verb+noun combinations (VNCs), and a method to use this information to improve VNC identification. Firstly, a sample of …...

AbstractLexicalized and hierarchical reordering models use relative frequencies of fully lexicalized phrase pairs to learn phrase reordering distributions. This results in unreliable estimation for infrequent phrase pairs which also tend …...

AbstractThis article describes the distributional strategy submitted by the Citius team to the SemEval 2017 Task 2. Even though the team participated in two subtasks, namely monolingual and cross-lingual word …...

This paper presents a two-step methodology to annotate temporally-anchored spatial knowledge on top of OntoNotes. We first generate potential knowledge using syntactic dependencies, and then crowdsource annotations to validate the …...

AbstractIn recent years, we have seen a colossal effort in pre-training multilingual text encoders using large-scale corpora in many languages to facilitate cross-lingual transfer learning. However, due to typological differences …...

AbstractPre-trained transformer-based models, such as BERT, have shown excellent performance in most natural language processing benchmark tests, but we still lack a good understanding of the linguistic knowledge of BERT …...

AbstractRecognizing and categorizing lexical collocations in context is useful for language learning, dictionary compilation and downstream NLP. However, it is a challenging task due to the varying degrees of frozenness …...