FrameNet is a linguistic knowledge graph containing information about lexical and predicate argument semantics of the English language. FrameNet contains two distinct entity classes: frames and lexical units, where a frame is a meaning and a lexical unit is a single meaning for a word.
434 PAPERS • NO BENCHMARKS YET
OntoNotes 5.0 is a large corpus comprising various genres of text (news, conversational telephone speech, weblogs, usenet newsgroups, broadcast, talk shows) in three languages (English, Chinese, and Arabic) with structural information (syntax and predicate argument structure) and shallow semantics (word sense linked to an ontology and coreference).
233 PAPERS • 12 BENCHMARKS
QA-SRL Bank 2.0 is a large-scale corpus of Question-Answer driven Semantic Role Labeling (QA-SRL) annotations. The corpus consists of over 250,000 question-answer pairs for over 64,000 sentences across 3 domains and was gathered with a new crowd-sourcing scheme that was shown to have high precision and good recall at modest cost.
6 PAPERS • NO BENCHMARKS YET
SRL is the task of extracting semantic predicate-argument structures from sentences. X-SRL is a multilingual parallel Semantic Role Labelling (SRL) corpus for English (EN), German (DE), French (FR) and Spanish (ES) that is based on English gold annotations and shares the same labelling scheme across languages.
4 PAPERS • NO BENCHMARKS YET
ExHVV is a novel dataset that offers natural language explanations of connotative roles for three types of entities -- heroes, villains, and victims, encompassing 4,680 entities present in 3K memes.
1 PAPER • NO BENCHMARKS YET
The corpus contains review sentences mostly of products in electronics domain, annotated and segregated into 4 comparison categories. Each comparison sentence is annotated with names of the products (PROD1 and PROD2), the aspect (ASP) and the predicate (PRED). Dataset contains sentences after auto-labeling on SNAP dataset and manually labeled sentences from the following corpora:
1 PAPER • 1 BENCHMARK