Triple

T6143431
Position Surface form Disambiguated ID Type / Status
Subject Orange S.A. E137016 entity
Predicate hasMainCompetitor P6615 FINISHED
Object SFR E326752 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: SFR | Statement: [Orange S.A., hasMainCompetitor, SFR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SFR
Context triple: [Orange S.A., hasMainCompetitor, SFR]
  • A. SFR chosen
    SFR is a major French telecommunications company providing mobile, internet, and television services.
  • B. SRF
    SRF is a French filmmakers' association best known for organizing the Directors' Fortnight sidebar at the Cannes Film Festival and advocating for directors' artistic and professional interests.
  • C. SRF
    SRF is the German-language division of the Swiss Broadcasting Corporation, responsible for producing and broadcasting radio, television, and online content in German-speaking Switzerland.
  • D. SFS
    SFS is a renowned Georgetown University school specializing in international affairs, diplomacy, and global policy education.
  • E. SFS
    SFS is the abbreviation for the Senior Foreign Service, the elite cadre of senior-ranking career diplomats in the United States Foreign Service.
  • 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_69c008a2c6308190a56519b22d55d083 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05cb50cb0819081ac64becf7aaf55 completed March 22, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c135f88db881908b8a5d9c35bf0fbb completed March 23, 2026, 12:45 p.m.
Created at: March 22, 2026, 4:16 p.m.