Triple

T21630479
Position Surface form Disambiguated ID Type / Status
Subject Rafael Márquez E533814 entity
Predicate leagueTitleWon P12322 FINISHED
Object Ligue 1 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: Ligue 1 | Statement: [Rafael Márquez, leagueTitleWon, Ligue 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ligue 1
Context triple: [Rafael Márquez, leagueTitleWon, 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 (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_69e0c464fba881908d0ff2ac80511ce1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef521679fc81909c94d42439fda4ba completed April 27, 2026, 12:09 p.m.
Created at: April 16, 2026, 6:34 p.m.