HIT at SemEval-2022 Task 2: Pre-trained Language Model for Idioms Detection

04/13/2022
by   Zheng Chu, et al.
0

The same multi-word expressions may have different meanings in different sentences. They can be mainly divided into two categories, which are literal meaning and idiomatic meaning. Non-contextual-based methods perform poorly on this problem, and we need contextual embedding to understand the idiomatic meaning of multi-word expressions correctly. We use a pre-trained language model, which can provide a context-aware sentence embedding, to detect whether multi-word expression in the sentence is idiomatic usage.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/02/2020

On the Sentence Embeddings from Pre-trained Language Models

Pre-trained contextual representations like BERT have achieved great suc...
research
04/21/2022

An Attention-Based Model for Predicting Contextual Informativeness and Curriculum Learning Applications

Both humans and machines learn the meaning of unknown words through cont...
research
11/24/2022

InDEX: Indonesian Idiom and Expression Dataset for Cloze Test

We propose InDEX, an Indonesian Idiom and Expression dataset for cloze t...
research
10/19/2021

Idiomatic Expression Identification using Semantic Compatibility

Idiomatic expressions are an integral part of natural language and const...
research
06/12/2018

Term Definitions Help Hypernymy Detection

Existing methods of hypernymy detection mainly rely on statistics over a...
research
07/23/2022

Context based lemmatizer for Polish language

Lemmatization is the process of grouping together the inflected forms of...
research
12/28/2015

Communicating with sentences: A multi-word naming game model

Naming game simulates the process of naming an object by a single word, ...

Please sign up or login with your details

Forgot password? Click here to reset