Add to ORKGIn this work we explore the possibility of training a neural network to classify and rank idiomatic expressions under constraints of data scarcity. We discuss our results comparing them both to other unsupervised models designed to perform idiom detection and to similar supervised classifiers trained to detect metaphoric bigrams
Idioms are multi-word expressions whose meaning cannot always be deduced from the literal meaning of...
Expressions can be ambiguous between idiomatic and literal interpretation depending on the context t...
Neural Machine Translation (NMT) has been widely used in recent years with significant improvements ...
In this work we explore the possibility of training a neural network to classify and rank idiomati...
The present work aims at automatically classifying Italian idiomatic and non-idiomatic phrases with ...
In this ablation study we observed whether the abstractness and ambiguity of idioms constitute key f...
Deep neural models, in particular Transformer-based pre-trained language models, require a significa...
Deep neural models, in particular Transformer-based pre-trained language models, require a significa...
An idiom is a multiword expression (MWE) whose meaning is non- compositional, i.e., the meaning of t...
Idiomatic expressions can be problematic for natural language processing applications as their meani...
In this thesis, we are concerned with idiomatic expressions and how to handle them within NLP. Idiom...
In this paper we assessed the cognitive plausibility of corpus-based flexibility measures for a sam...
This thesis presents resources capable of enhancing solutions of some Natural Language Processing (N...
The goal of this work is to assess the cognitive plausibility of corpus-based measures that capture ...
Idiom token classification is the task of deciding for a set of potentially idiomatic phrases whethe...
Idioms are multi-word expressions whose meaning cannot always be deduced from the literal meaning of...
Expressions can be ambiguous between idiomatic and literal interpretation depending on the context t...
Neural Machine Translation (NMT) has been widely used in recent years with significant improvements ...
In this work we explore the possibility of training a neural network to classify and rank idiomati...
The present work aims at automatically classifying Italian idiomatic and non-idiomatic phrases with ...
In this ablation study we observed whether the abstractness and ambiguity of idioms constitute key f...
Deep neural models, in particular Transformer-based pre-trained language models, require a significa...
Deep neural models, in particular Transformer-based pre-trained language models, require a significa...
An idiom is a multiword expression (MWE) whose meaning is non- compositional, i.e., the meaning of t...
Idiomatic expressions can be problematic for natural language processing applications as their meani...
In this thesis, we are concerned with idiomatic expressions and how to handle them within NLP. Idiom...
In this paper we assessed the cognitive plausibility of corpus-based flexibility measures for a sam...
This thesis presents resources capable of enhancing solutions of some Natural Language Processing (N...
The goal of this work is to assess the cognitive plausibility of corpus-based measures that capture ...
Idiom token classification is the task of deciding for a set of potentially idiomatic phrases whethe...
Idioms are multi-word expressions whose meaning cannot always be deduced from the literal meaning of...
Expressions can be ambiguous between idiomatic and literal interpretation depending on the context t...
Neural Machine Translation (NMT) has been widely used in recent years with significant improvements ...