Triple

T12207488
Position Surface form Disambiguated ID Type / Status
Subject CycleGAN E290871 entity
Predicate publishedAtConference P21395 FINISHED
Object ICCV 2017 E91276 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: ICCV 2017 | Statement: [CycleGAN, publishedAtConference, ICCV 2017]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ICCV 2017
Context triple: [CycleGAN, publishedAtConference, ICCV 2017]
  • A. IEEE International Conference on Computer Vision chosen
    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.
  • B. 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.
  • C. European Conference on Computer Vision
    The European Conference on Computer Vision (ECCV) is a leading biennial research conference that showcases cutting-edge advances in computer vision and pattern recognition.
  • D. ICPR
    ICPR is an international organization dedicated to protecting and improving the ecological health and water quality of the Rhine River and its basin.
  • E. ICLR
    ICLR (International Conference on Learning Representations) is a leading annual machine learning conference focused on deep learning and representation learning research.
  • 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_69d6ab65923081909acfc61b7a612233 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c7d8f5c8190a46e9caa2a920fa9 completed April 10, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a9d2f0c81908352cd9f0167c6ab completed May 2, 2026, 2:30 p.m.
Created at: April 8, 2026, 9:51 p.m.