Triple

T1735996
Position Surface form Disambiguated ID Type / Status
Subject SNCF E37919 entity
Predicate brand P1500 FINISHED
Object Intercités E39984 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: Intercités | Statement: [SNCF, brand, Intercités]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Intercités
Context triple: [SNCF, brand, Intercités]
  • A. Intercités chosen
    Intercités is a network of French long-distance conventional trains operated by SNCF, connecting major cities and regions across the country.
  • B. SNCF Voyageurs
    SNCF Voyageurs is the passenger rail operating division of France’s national railway company, responsible for running high-speed, regional, and commuter train services.
  • C. Transport Express Régional
    Transport Express Régional is a network of regional passenger trains in France operated by SNCF, providing local and intercity rail services across most French regions.
  • D. Eurostar
    Eurostar is a high-speed international train service connecting the United Kingdom with mainland Europe via the Channel Tunnel, linking cities such as London, Paris, and Brussels.
  • E. Ouigo
    Ouigo is a low-cost high-speed train service operated by France's SNCF, offering budget TGV travel with simplified onboard services.
  • 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_69a8861cc6ac8190ac0b2e31ccf62851 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63a369048190bae352573f5082f1 completed March 6, 2026, 5:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69addf39b08881908d798b3eae51dbae completed March 8, 2026, 8:42 p.m.
Created at: March 4, 2026, 7:30 p.m.