Triple

T10937617
Position Surface form Disambiguated ID Type / Status
Subject Ronan O'Gara E258376 entity
Predicate playedForClub P2168 FINISHED
Object Racing Métro 92 E725397 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: Racing Métro 92 | Statement: [Ronan O'Gara, playedForClub, Racing Métro 92]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Racing Métro 92
Context triple: [Ronan O'Gara, playedForClub, Racing Métro 92]
  • A. Racing Métro 92 chosen
    Racing Métro 92 was the former name of the professional French rugby union club now known as Racing 92, based in the Paris region and competing in the Top 14.
  • B. Le Racing
    Le Racing is the popular nickname of RC Strasbourg Alsace, a historic French football club based in Strasbourg.
  • C. Le Mans FC
    Le Mans FC is a French professional football club based in the city of Le Mans, known for competing in the French football league system and playing its home matches at the MMArena.
  • D. TGV Paris–Nice
    TGV Paris–Nice is a high-speed French train service connecting Paris with the Mediterranean city of Nice.
  • E. Paris–Toulouse
    Paris–Toulouse is a major intercity rail corridor in France linking the capital Paris with the southwestern city of Toulouse.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770b065288190b4216beee8e8a193 completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23bfd6a108190a0557598f68659fa completed April 17, 2026, 1:56 p.m.
Created at: April 8, 2026, 9:23 p.m.