Triple

T2828488
Position Surface form Disambiguated ID Type / Status
Subject Bruxelles-Midi / Brussel-Zuid E54979 entity
Predicate servedBy P82 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: [Bruxelles-Midi / Brussel-Zuid, servedBy, TGV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TGV
Context triple: [Bruxelles-Midi / Brussel-Zuid, servedBy, TGV]
  • A. TGV Ouigo
    TGV Ouigo is a low-cost high-speed train service operated by SNCF in France, offering budget fares on selected TGV routes.
  • B. Bezannes TGV
    Bezannes TGV is a tram terminus and transport hub in the suburb of Bezannes serving the high-speed TGV rail connections near Reims, France.
  • C. 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.
  • D. TGV inOui
    TGV inOui is SNCF’s premium high-speed train service in France, offering upgraded comfort and amenities on major routes including those served by the LGV Méditerranée line.
  • E. Intercités
    Intercités is a network of French long-distance conventional trains operated by SNCF, connecting major cities and regions across the country.
  • 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde97168c8190b31122b2ad9fdebf completed March 7, 2026, 8:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8bb92b08190b1de7e6973d96301 completed March 10, 2026, 9:47 a.m.
Created at: March 6, 2026, 9:59 p.m.