Triple

T871400
Position Surface form Disambiguated ID Type / Status
Subject Greg Yang E18820 entity
Predicate hasGivenTalkAt P10206 FINISHED
Object ICLR E95182 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: ICLR | Statement: [Greg Yang, hasGivenTalkAt, ICLR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ICLR
Context triple: [Greg Yang, hasGivenTalkAt, ICLR]
  • A. ICLR chosen
    ICLR (International Conference on Learning Representations) is a leading annual machine learning conference focused on deep learning and representation learning research.
  • B. ICML
    ICML (International Conference on Machine Learning) is one of the premier global academic conferences focused on research in machine learning and related fields.
  • C. NeurIPS
    NeurIPS is a premier international conference focused on advances in machine learning, artificial intelligence, and computational neuroscience.
  • D. IEEE International Conference on Computer Vision
    The IEEE International Conference on Computer Vision (ICCV) is a premier biennial research conference that showcases cutting-edge advances in computer vision and pattern recognition.
  • E. IEEE Computer Society Conference on Computer Vision and Pattern Recognition
    The IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) is a premier annual international research conference showcasing cutting-edge advances in computer vision, machine learning, and pattern recognition.
  • 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_69a4938db1f081909bcd1ad2713b6096 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2b8063081909566c404ca63a29e completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7b84dcf748190b20372fdc48d6766 completed March 4, 2026, 4:42 a.m.
Created at: March 1, 2026, 7:39 p.m.