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

Showing 7180 of 160 papers

TitleStatusHype
GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment AnalysisCode1
What if we had no Wikipedia? Domain-independent Term Extraction from a Large News Corpus0
Categorisation of Bulgarian Legislative Documents0
Relation-Aware Collaborative Learning for Unified Aspect-Based Sentiment AnalysisCode1
Predicting Degrees of Technicality in Automatic Terminology Extraction0
Octet: Online Catalog Taxonomy Enrichment with Self-Supervision0
Unsupervised Neural Aspect Search with Related Terms Extraction0
Developing an Arabic Infectious Disease Ontology to Include Non-Standard Terminology0
Dataset Creation and Evaluation of Aspect Based Sentiment Analysis in Telugu, a Low Resource Language0
A Term Extraction Approach to Survey Analysis in Health Care0
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Benchmark Results

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