Triple

T13651630
Position Surface form Disambiguated ID Type / Status
Subject SFR E326752 entity
Predicate hasCompetitor P1375 FINISHED
Object Bouygues Telecom E132001 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: Bouygues Telecom | Statement: [SFR, hasCompetitor, Bouygues Telecom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bouygues Telecom
Context triple: [SFR, hasCompetitor, Bouygues Telecom]
  • A. France Télécom
    France Télécom was the former state-owned French telecommunications company that evolved into Orange S.A., a major global telecom operator.
  • B. Télécom Bretagne
    Télécom Bretagne was a leading French grande école and engineering school specializing in telecommunications and information technologies, later integrated into IMT Atlantique.
  • C. Bouygues chosen
    Bouygues is a major French industrial group primarily active in construction, real estate development, media, and telecommunications.
  • D. Free (French telecommunications company)
    Free is a major French telecommunications operator known for its low-cost, disruptive internet and mobile offers that helped transform France’s telecom market.
  • E. Deutsche Telekom
    Deutsche Telekom is a major German telecommunications company and one of the largest telecom providers in Europe, offering mobile, fixed-line, and internet services worldwide.
  • 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_69d8076d8270819092afc2f0e9c359a8 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc609676c8190b5b1cabe6b315142 completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78affa3c481909dba71e2ce9f44c1 completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:52 p.m.