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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 141–150 of 160 papers

TitleStatusHype
Automatic Term Extraction Combining Different Information (Extraction automatique de termes combinant diff\'erentes informations) [in French]—0
Automatic Term Extraction from Newspaper Corpora: Making the Most of Specificity and Common Features—0
Automatic Term Recognition Needs Multiple Evidence—0
AWARE: Aspect-Based Sentiment Analysis Dataset of Apps Reviews for Requirements Elicitation—0
BAN-ABSA: An Aspect-Based Sentiment Analysis dataset for Bengali and it's baseline evaluation—0
Bootstrapping Term Extractors for Multiple Languages—0
Building and Applying Profiles Through Term Extraction—0
Categorisation of Bulgarian Legislative Documents—0
CoastTerm: a Corpus for Multidisciplinary Term Extraction in Coastal Scientific Literature—0
Comparative Study of Domain Driven Terms Extraction Using Large Language Models—0
Show:102550
← PrevPage 15 of 16Next →
All datasetsAWARESemEval 2014 Task 4 Laptop

Benchmark Results

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