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 71–80 of 160 papers

TitleStatusHype
A Joint Training Dual-MRC Framework for Aspect Based Sentiment Analysis—0
Constituency Lattice Encoding for Aspect Term ExtractionCode0
BAN-ABSA: An Aspect-Based Sentiment Analysis dataset for Bengali and it's baseline evaluation—0
Graph Based Automatic Domain Term Extraction—0
Aspect-Based Argument MiningCode0
Enhancing Aspect Term Extraction with Soft Prototypes—0
Automatic Extraction of Agriculture Terms from Domain Text: A Survey of Tools and Techniques—0
What if we had no Wikipedia? Domain-independent Term Extraction from a Large News Corpus—0
Categorisation of Bulgarian Legislative Documents—0
Predicting Degrees of Technicality in Automatic Terminology Extraction—0
Show:102550
← PrevPage 8 of 16Next →
All datasetsAWARESemEval 2014 Task 4 Laptop

Benchmark Results

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