Triple

T19431544
Position Surface form Disambiguated ID Type / Status
Subject Valenciennes FC E486124 entity
Predicate hasPlayedInLeague P2209 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: [Valenciennes FC, hasPlayedInLeague, Ligue 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ligue 1
Context triple: [Valenciennes FC, hasPlayedInLeague, 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_69d8e8d688f881909c85104a62e09d8a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6335b4e388190913ded15ad165b7b completed April 20, 2026, 2:08 p.m.
Created at: April 10, 2026, 1:37 p.m.