Triple

T3444038
Position Surface form Disambiguated ID Type / Status
Subject Dijon E72631 entity
Predicate hasSportsTeam P330 FINISHED
Object Dijon FCO E296160 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: Dijon FCO | Statement: [Dijon, hasSportsTeam, Dijon FCO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dijon FCO
Context triple: [Dijon, hasSportsTeam, Dijon FCO]
  • A. Dijon FCO chosen
    Dijon FCO is a French professional football club based in Dijon, known for competing in the country’s top divisions and maintaining regional rivalries, including with AJ Auxerre.
  • B. Vinci Airports
    Vinci Airports is a global airport operator that manages and develops a large network of airports across multiple countries as part of the Vinci Group’s transport infrastructure portfolio.
  • C. Ajaccio Napoleon Bonaparte Airport
    Ajaccio Napoleon Bonaparte Airport is the main commercial airport serving the city of Ajaccio and the surrounding region on the French island of Corsica.
  • D. Strasbourg Airport
    Strasbourg Airport is an international airport serving the city of Strasbourg and the surrounding Alsace region in northeastern France.
  • E. Chambéry Airport
    Chambéry Airport is a regional airport in southeastern France that primarily serves the city of Chambéry and nearby Alpine ski destinations.
  • 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_69ad85b05c848190b7a28ceec2bd7b74 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adba2a605c8190a0eafdf6f25b1e38 completed March 8, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360da33e081908630e3f29ea01530 completed March 13, 2026, 12:56 a.m.
Created at: March 8, 2026, 3:16 p.m.