Triple

T13036008
Position Surface form Disambiguated ID Type / Status
Subject Free Mobile E326561 entity
Predicate networkSharing P66218 FINISHED
Object national roaming on Orange France network LITERAL 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: national roaming on Orange France network | Statement: [Free Mobile, networkSharing, national roaming on Orange France network]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: networkSharing
Context triple: [Free Mobile, networkSharing, national roaming on Orange France network]
  • A. network
    Indicates that one entity is connected to or interacts with another through a system of relationships, communication, or information exchange.
  • B. sharesBorderingNetworkWith
    Indicates that two entities are connected through adjacent or directly neighboring positions within the same network structure.
  • C. networkSection
    Indicates that one entity represents a specific section, segment, or subdivision within a larger network structure.
  • D. networkBand
    Indicates the specific frequency band or range within a network over which communication or data transmission occurs.
  • E. inNetwork chosen
    Indicates that one entity is within the same defined network, system, or coverage group as another entity, such that network-based interactions or benefits apply between them.
  • F. None of above.

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.
PD Predicate disambiguation batch_69d97dc39a0881908119c62e31bf6182 completed April 10, 2026, 10:46 p.m.
Created at: April 9, 2026, 8:55 p.m.