Triple

T294406
Position Surface form Disambiguated ID Type / Status
Subject Gare du Nord E6061 entity
Predicate railwayLine P848 FINISHED
Object TGV E11761 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: TGV | Statement: [Gare du Nord, railwayLine, TGV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TGV
Context triple: [Gare du Nord, railwayLine, TGV]
  • A. TGV high-speed rail chosen
    TGV high-speed rail is France’s flagship high-speed train service that connects major cities and hubs, including direct links from Charles de Gaulle Airport to destinations across the country and into neighboring nations.
  • B. 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.
  • C. Thalys
    Thalys is a high-speed international train service connecting major cities in France, Belgium, the Netherlands, and Germany.
  • D. 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.
  • E. Léman Express
    Léman Express is a cross-border regional rail network linking Geneva with surrounding areas in Switzerland and France as part of the Léman metropolitan transport system.
  • 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_69a2e79114b081909490b3bf5a5dbb51 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2e978420881908488df342a7d5e90 completed Feb. 28, 2026, 1:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3b47185f48190813159f932c0af9a completed March 1, 2026, 3:37 a.m.
Created at: Feb. 28, 2026, 1:06 p.m.