Home › Datasets › task › Entity Typing
Entity Typing datasets
archive 2025-07-28
12 datasets carry the task tag "Entity Typing" (the task itself: Entity Typing), ordered by the archive's paper count. Page 1 of 1: 12 shown of 12. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
Entity Typing datasets 1–12 of 12
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…
254 papers · 12 benchmarks
The CoNLL dataset is a widely used resource in the field of natural language processing (NLP).
187 papers · 35 benchmarks
FIGER (Fine-Grained Entity Recognition)
The FIGER dataset is an entity recognition dataset where entities are labelled using fine-grained system 112 tags, such as person/doctor, art/writtenwork and building/hotel.
96 papers · 2 benchmarks
Few-NERD is a large-scale, fine-grained manually annotated named entity recognition dataset, which contains 8 coarse-grained types, 66 fine-grained types, 188,200 sentences, 491,711 entities, and 4,601,223 tokens.
77 papers · 3 benchmarks
AIDA CoNLL-YAGO contains assignments of entities to the mentions of named entities annotated for the original CoNLL 2003 entity recognition task.
64 papers · 0 benchmarks
The Open Entity dataset is a collection of about 6,000 sentences with fine-grained entity types annotations.
35 papers · 2 benchmarks
A large-scale English dataset for coreference resolution.
20 papers · 1 benchmark
GUM (Georgetown University Multilayer corpus)
GUM is an open source multilayer English corpus of richly annotated texts from twelve text types.
13 papers · 1 benchmark
A dataset for fine-grained entity typing of knowledge graph entities built from Freebase.
8 papers · 0 benchmarks
WikiSRS is a novel dataset of similarity and relatedness judgments of paired Wikipedia entities (people, places, and organizations), as assigned by Amazon Mechanical Turk workers.
2 papers · 0 benchmarks
The DocRED Information Extraction (DocRED-IE) dataset extends the DocRED dataset for the Document-level Closed Information Extraction (DocIE) task.
1 paper · 6 benchmarks
HTDM (Hypertention Disease Medication)
Hypertention Disease Medication dataset.
1 paper · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.