Triple

T15951930
Position Surface form Disambiguated ID Type / Status
Subject TGV V150 E386837 entity
Predicate participatingOrganizations P66747 FINISHED
Object SNCF E37919 NE FINISHED

How this triple was built (3 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: SNCF | Statement: [TGV V150, participatingOrganizations, SNCF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SNCF
Context triple: [TGV V150, participatingOrganizations, SNCF]
  • A. SNCF chosen
    SNCF is France’s national state-owned railway company, responsible for operating the country’s passenger and freight rail services and much of its rail infrastructure.
  • B. SNCF Réseau
    SNCF Réseau is the French state-owned rail infrastructure manager responsible for operating, maintaining, and developing France’s national railway network.
  • C. SNCF Sud-Est region
    The SNCF Sud-Est region was a major operating division of the French national railway company responsible for managing and running rail services in the southeastern part of France, including key routes linking Paris with Lyon and the Mediterranean.
  • D. OUIGO
    OUIGO is a low-cost high-speed train service operated by France’s national railway company SNCF, offering budget-friendly travel on major routes.
  • E. Francorail
    Francorail was a French railway manufacturing consortium known for producing high-speed trainsets, including early models of the TGV.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: participatingOrganizations
Context triple: [TGV V150, participatingOrganizations, SNCF]
  • A. involvedOrganizations chosen
    Indicates that there is a participation or engagement relationship between an entity and one or more organizations in the context of a specific event, activity, or project.
  • B. contributingOrganization
    Indicates an organization that plays a role in creating, supporting, or otherwise contributing to the production or provision of something.
  • C. targetOrganizations
    Indicates the organizations that are the intended recipients or focus of an action, initiative, or influence.
  • D. hasAuxiliaryOrganizations
    Indicates that an entity is associated with one or more subsidiary or supporting organizations that assist or extend its activities.
  • E. sectoralOrganizations
    Indicates that there is an organizational relationship specifically structured around a particular sector or industry.
  • F. None of above.

Provenance (4 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_69d86da882448190a82ea962fe343b79 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e17d4d08f481909f38b75e3f42d9ab completed April 17, 2026, 12:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf16b1b881909768d18b889260da completed May 10, 2026, 12:19 a.m.
PD Predicate disambiguation batch_69e142d37cd88190ab50760f1783e20c completed April 16, 2026, 8:13 p.m.
Created at: April 10, 2026, 4:53 a.m.