Claim · 2019-11-04 · event · Stated in source · Supported

Witteveen and Andrews (2019) use "large language models" for neural language models such as GPT-2.

One recorded claim. The claim panel gives its qualification, the source passages with their place in each source, and how it was checked.

What it connects

Paraphrasing with Large Language Models → uses the name →

Where it appears

No collection page holds this claim. It is listed with its records in the explorer.

Claim and evidence

Paraphrasing with Large Language Modelsuses the name ↓

Machine-checked, not reviewed by an editorStated in sourceSupported

Supporting evidence: primary · 1 source

Date: 2019-11-04 · event Records dated 2019 →

Scope and limitsThe earliest located use in the neural sense by the ACL Anthology title and abstract search for 2008–2019; two other 2019 Anthology abstracts also use the phrase. Not evidence of coinage of the neural sense.

The evidence 02

primary sourceSupports the claim

Paraphrasing with Large Language Models

Association for Computational Linguistics (ACL Anthology) · Publication date unknown

Cite the original source

Cite the original document, not Selekoa. Check these details against it.

Source excerpt

“Paraphrasing with Large Language Models”

Location in source PDF p. 1, title

How it was read Retrieved directly from the publisher

Machine-checked · 2026-10-31

Source details and check notes

Authors: Sam Witteveen; Martin Andrews
Version: Retrieved for the candidate pack on 2026-10-29 (SHA-256 9149c5ebbf6cc351c6ec2571fb244b10b6aff2b383c047aa1d69d9d447db2498). WNGT 2019 workshop proceedings PDF as hosted by the ACL Anthology (D19-5623)
Canonical address: Open the canonical source ↗
Accessed: 2026-10-29
Language: English (en)
Attribution: Sam Witteveen, Martin Andrews, “Paraphrasing with Large Language Models”.
Reuse: No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution.
Check notes: Candidate pack passage, Kinds of AI and technical history (research/technical-history). The quotation (5 words) matched the text retrieved for the candidate pack on 2026-10-29. Matching ignored differences of whitespace, case, quotation marks, dashes, PDF line-break hyphens and Unicode compatibility forms, so the source’s typography can differ. No human editorial review.

primary sourceSupports the claim

Paraphrasing with Large Language Models

Association for Computational Linguistics (ACL Anthology) · Publication date unknown

Cite the original source

Cite the original document, not Selekoa. Check these details against it.

Source excerpt

“Recently, large language models such as GPT2 have shown themselves to be extremely adept at text generation”

Location in source PDF p. 1, introduction

How it was read Retrieved directly from the publisher

Machine-checked · 2026-10-31

Source details and check notes

Authors: Sam Witteveen; Martin Andrews
Version: Retrieved for the candidate pack on 2026-10-29 (SHA-256 9149c5ebbf6cc351c6ec2571fb244b10b6aff2b383c047aa1d69d9d447db2498). WNGT 2019 workshop proceedings PDF as hosted by the ACL Anthology (D19-5623)
Canonical address: Open the canonical source ↗
Accessed: 2026-10-29
Language: English (en)
Attribution: Sam Witteveen, Martin Andrews, “Paraphrasing with Large Language Models”.
Reuse: No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution.
Check notes: Candidate pack passage, Kinds of AI and technical history (research/technical-history). The quotation (17 words) matched the text retrieved for the candidate pack on 2026-10-29. Matching ignored differences of whitespace, case, quotation marks, dashes, PDF line-break hyphens and Unicode compatibility forms, so the source’s typography can differ. No human editorial review.

Status and meaning

Editorial status. Not reviewed by an editor. An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.

Relation. A passage of the document uses a name for a family of methods or a term, in the sense the concept’s naming criterion describes or, where labelled, in another sense. The record documents the use; it is not evidence that the name began there, and it implies no influence on or from another text.

Date. Dates of the conference the text is associated with, as its proceedings or organiser state them; no retrieved text dates an individual presentation.

Record ID th-term-llm-witteveen-2019