Triple

T16355868
Position Surface form Disambiguated ID Type / Status
Subject Greg Vanney E397176 entity
Predicate leaguePlayedIn P2209 FINISHED
Object Ligue 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: Ligue 1 | Statement: [Greg Vanney, leaguePlayedIn, Ligue 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ligue 1
Context triple: [Greg Vanney, leaguePlayedIn, Ligue 1]
  • A. 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.
  • B. Ligue 1
    Ligue 1 is the top professional football division in Tunisia, featuring the country’s leading clubs in the national league system.
  • C. 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.
  • D. French League
    The French League is France's top-tier professional basketball championship, featuring the country's leading clubs competing for the national title.
  • E. 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.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2face3a54819099418edd0eecc963 completed April 18, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002dbaacd88190b2c90c5be2832307 completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:07 a.m.