Triple

T4651220
Position Surface form Disambiguated ID Type / Status
Subject Language Models are Few-Shot Learners E102297 entity
Predicate publisher P29 FINISHED
Object NeurIPS 2020 E96742 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: NeurIPS 2020 | Statement: [Language Models are Few-Shot Learners, publisher, NeurIPS 2020]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NeurIPS 2020
Context triple: [Language Models are Few-Shot Learners, publisher, NeurIPS 2020]
  • A. NeurIPS chosen
    NeurIPS is a premier international conference focused on advances in machine learning, artificial intelligence, and computational neuroscience.
  • B. NIPS
    NIPS is the acronym for the Northern Ireland Prison Service, the government agency responsible for managing prisons and overseeing the custody and rehabilitation of offenders in Northern Ireland.
  • C. ICLR
    ICLR (International Conference on Learning Representations) is a leading annual machine learning conference focused on deep learning and representation learning research.
  • D. ICML
    ICML (International Conference on Machine Learning) is one of the premier global academic conferences focused on research in machine learning and related fields.
  • E. NeurIPS Test of Time Award
    The NeurIPS Test of Time Award is a prestigious honor given at the NeurIPS conference to recognize influential machine learning and AI research papers that have had lasting impact over many years.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69bd43d71a308190afea7280841b0de8 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd630343f88190954d19fcd18a5864 completed March 20, 2026, 3:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69be0374967c8190b77bcd3ea1c4d59d completed March 21, 2026, 2:33 a.m.
Created at: March 20, 2026, 1:14 p.m.