SOTAVerified

Term Extraction

Term Extraction, or Automated Term Extraction (ATE), is about extraction domain-specific terms from natural language text. For example, the sentence “We meta-analyzed mortality using random-effect models” contains the domain-specific single-word terms "meta-analyzed", "mortality" and the multi-word term "random-effect models".

Papers

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Showing 61–70 of 160 papers

TitleStatusHype
Distributional semantic modeling: a revised technique to train term/word vector space models applying the ontology-related approach—0
DLIREC: Aspect Term Extraction and Term Polarity Classification System—0
A Dataset for Term Extraction in Hindi—0
Automatic Term Extraction from Newspaper Corpora: Making the Most of Specificity and Common Features—0
Enhancing Automatic Term Extraction with Large Language Models via Syntactic Retrieval—0
Enhancing Aspect Term Extraction with Soft Prototypes—0
Automatic Term Extraction Combining Different Information (Extraction automatique de termes combinant diff\'erentes informations) [in French]—0
A Self-enhancement Multitask Framework for Unsupervised Aspect Category Detection—0
Ensembling Transformers for Cross-domain Automatic Term Extraction—0
Efficient Terminology Integration for LLM-based Translation in Specialized Domains—0
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All datasetsAWARESemEval 2014 Task 4 Laptop

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BaselineF1-Score0.82—Unverified
#ModelMetricClaimedVerifiedStatus
1Seq2Seq4ATEF1-Score0.8—Unverified