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Table-to-Text Generation datasets

archive 2025-07-28

6 datasets carry the task tag "Table-to-Text Generation" (the task itself: Table-to-Text Generation), ordered by the archive's paper count. Page 1 of 1: 6 shown of 6. 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

Table-to-Text Generation datasets 1–6 of 6

The WebNLG corpus comprises of sets of triplets describing facts (entities and relations between them) and the corresponding facts in form of natural language text.
149 papers · 17 benchmarks
E2E (End-to-End NLG Challenge)
End-to-End NLG Challenge (E2E) aims to assess whether recent end-to-end NLG systems can generate more complex output by learning from datasets containing higher lexical richness, syntactic complexity and diverse discourse phenomena.
90 papers · 4 benchmarks
WikiBio (Wikipedia Biography Dataset)
This dataset gathers 728,321 biographies from English Wikipedia.
84 papers · 1 benchmark
This dataset consists of (human-written) NBA basketball game summaries aligned with their corresponding box- and line-scores.
65 papers · 5 benchmarks
DART is a large dataset for open-domain structured data record to text generation.
45 papers · 3 benchmarks
This dataset gathers 428,748 person and 12,236 animal infobox with descriptions based on Wikipedia dump (2018/04/01) and Wikidata (2018/04/12).
5 papers · 3 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.