Triple

T13036022
Position Surface form Disambiguated ID Type / Status
Subject Station F E326562 entity
Predicate ownedBy P347 FINISHED
Object Xavier Niel E64957 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: Xavier Niel | Statement: [Station F, ownedBy, Xavier Niel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xavier Niel
Context triple: [Station F, ownedBy, Xavier Niel]
  • A. Xavier Niel chosen
    Xavier Niel is a French billionaire entrepreneur and investor best known as the founder of the telecom company Iliad/Free and a prominent figure in France’s technology and startup ecosystem.
  • B. Martin Bouygues
    Martin Bouygues is a French businessman best known as the longtime chairman and CEO of the Bouygues industrial group, active in construction, media, and telecommunications.
  • C. Francis Bouygues
    Francis Bouygues was a French entrepreneur and engineer best known as the founder of the Bouygues construction and telecommunications conglomerate.
  • D. Philippe Kahn
    Philippe Kahn is a French technology entrepreneur and software engineer best known for founding Borland and inventing the first camera phone solution.
  • E. Nicolas Vanier
    Nicolas Vanier is a French adventurer, filmmaker, and writer known for his expeditions in cold regions and his nature-focused films and books.
  • 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_69d8076cc45c81908123123f43e69266 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97f2a71a0819098bb6cf8a4b2208a completed April 10, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5c5155c8190b2c4e5bbcdaadc47 completed May 3, 2026, 7:14 a.m.
Created at: April 9, 2026, 8:55 p.m.