Triple

T14106196
Position Surface form Disambiguated ID Type / Status
Subject TF1 E339510 entity
Predicate cableService P48296 FINISHED
Object Numericable-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: Numericable-SFR | Statement: [TF1, cableService, Numericable-SFR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Numericable-SFR
Context triple: [TF1, cableService, Numericable-SFR]
  • A. SFR chosen
    SFR is a major French telecommunications company providing mobile, internet, and television services.
  • B. Numéro
    Numéro is a French international fashion magazine known for its high-end editorial photography and coverage of luxury fashion, art, and culture.
  • C. SMF
    SMF (System Management Facilities) is an IBM z/OS component that collects and records system and workload performance data for monitoring, accounting, and capacity planning.
  • D. SMF
    SMF is the three-letter IATA airport code for Sacramento International Airport, the primary commercial airport serving California’s capital city.
  • E. Nnssf
    Nnssf is a 5G core network service-based interface used by network functions to interact with the Network Slice Selection Function (NSSF) for slice selection and related operations.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de600ada808190b92d67dc30f13d15 completed April 14, 2026, 3:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0b48e448190b4fb8cb33e5d97e6 completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:22 p.m.