Triple

T17694036
Position Surface form Disambiguated ID Type / Status
Subject Hindsight Experience Replay E441111 entity
Predicate publishedAt P30105 FINISHED
Object NIPS 2017 NE NERFINISHED

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: NIPS 2017 | Statement: [Hindsight Experience Replay, publishedAt, NIPS 2017]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NIPS 2017
Context triple: [Hindsight Experience Replay, publishedAt, NIPS 2017]
  • A. 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.
  • B. NeurIPS chosen
    NeurIPS is a premier international conference focused on advances in machine learning, artificial intelligence, and computational neuroscience.
  • 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. “Large-Scale Machine Learning with Stochastic Gradient Descent”
    “Large-Scale Machine Learning with Stochastic Gradient Descent” is a widely cited work by Léon Bottou that analyzes and advocates stochastic gradient descent as an efficient optimization method for large-scale machine learning problems.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9e940b081908b862bb0e6e89b0d completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4715485d88190b9b6f347ff85d7c7 completed April 19, 2026, 6:08 a.m.
Created at: April 10, 2026, 10:04 a.m.