Triple

T4085099
Position Surface form Disambiguated ID Type / Status
Subject R68 subway car E87570 entity
Predicate manufacturer P490 FINISHED
Object Francorail E432617 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: Francorail | Statement: [R68 subway car, manufacturer, Francorail]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Francorail
Context triple: [R68 subway car, manufacturer, Francorail]
  • A. Francorail chosen
    Francorail was a French railway manufacturing consortium known for producing high-speed trainsets, including early models of the TGV.
  • B. SNCF
    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.
  • C. SNCF Réseau
    SNCF Réseau is the French state-owned rail infrastructure manager responsible for operating, maintaining, and developing France’s national railway network.
  • D. SNCF Connect
    SNCF Connect is the official digital platform and app of the French national railway company, providing online ticket booking, travel planning, and real-time information for trains and other transport services.
  • E. 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.
  • 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_69aed9435cf48190ad1da737c962d19d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc7b7cc4819089cfbf2b1c23ccc5 completed March 9, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e4d20dd0819080773876f6198250 completed March 14, 2026, 10:44 p.m.
Created at: March 9, 2026, 3:39 p.m.