Triple

T16985087
Position Surface form Disambiguated ID Type / Status
Subject Dieter Müller E412042 entity
Predicate playedIn P2170 FINISHED
Object French Division 1 E66666 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: French Division 1 | Statement: [Dieter Müller, playedIn, French Division 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: French Division 1
Context triple: [Dieter Müller, playedIn, French Division 1]
  • A. Ligue 1 and Ligue 2
    Ligue 1 and Ligue 2 are the top two professional divisions of French football, forming the elite tiers of the national league system.
  • B. Ligue A (France)
    Ligue A (France) is the top professional men's volleyball league in France, featuring the country's leading clubs in the sport.
  • C. Ligue 2
    Ligue 2 is the second tier of professional football in the French league system, sitting directly below Ligue 1.
  • D. Ligue 1 chosen
    Ligue 1 is France’s top professional football division, featuring the country’s leading clubs in the highest tier of its league system.
  • E. Ligue 1
    Ligue 1 is the top professional football division in Tunisia, featuring the country’s leading clubs in the national league system.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d18af95c8190a25ef0614e1a17f3 completed April 18, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc1109a081908890bbd5958c76c2 completed May 10, 2026, 7:27 p.m.
Created at: April 10, 2026, 5:32 a.m.