Triple

T20079770
Position Surface form Disambiguated ID Type / Status
Subject Blaise Matuidi E499965 entity
Predicate leaguePlayedIn 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: [Blaise Matuidi, leaguePlayedIn, Ligue 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ligue 1
Context triple: [Blaise Matuidi, 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 (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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6643f93208190ae2a413f88ea9aed completed April 20, 2026, 5:37 p.m.
Created at: April 11, 2026, 3:40 p.m.