Triple

T15951912
Position Surface form Disambiguated ID Type / Status
Subject TGV V150 E386837 entity
Predicate basedOn P98 FINISHED
Object TGV POS
TGV POS is a high-speed French TGV trainset designed for international services, notably operating on routes between France, Germany, and Switzerland.
 E1186567 NE FINISHED

How this triple was built (4 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 POS | Statement: [TGV V150, basedOn, TGV POS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TGV POS
Context triple: [TGV V150, basedOn, TGV POS]
  • A. 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.
  • 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 PSE
    TGV PSE is the original generation of French high-speed TGV Sud-Est trainsets that inaugurated high-speed rail service in France.
  • D. TGV
    TGV is France’s high-speed intercity train service, renowned for rapid connections between major cities such as Paris and Lille.
  • E. TGV INOUI
    TGV INOUI is SNCF’s premium high-speed train service in France, offering upgraded comfort, amenities, and service compared to standard TGV trains.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: TGV POS
Triple: [TGV V150, basedOn, TGV POS]
Generated description
TGV POS is a high-speed French TGV trainset designed for international services, notably operating on routes between France, Germany, and Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TGV POS
Target entity description: TGV POS is a high-speed French TGV trainset designed for international services, notably operating on routes between France, Germany, and Switzerland.
  • A. 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.
  • 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 PSE
    TGV PSE is the original generation of French high-speed TGV Sud-Est trainsets that inaugurated high-speed rail service in France.
  • D. TGV
    TGV is France’s high-speed intercity train service, renowned for rapid connections between major cities such as Paris and Lille.
  • E. TGV INOUI
    TGV INOUI is SNCF’s premium high-speed train service in France, offering upgraded comfort, amenities, and service compared to standard TGV trains.
  • F. None of above. chosen

Provenance (5 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_69e156d59f5081909f6a81d578c4e2e8 completed April 16, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe7ab070819090232efdeecdd5fb completed May 9, 2026, 11:08 p.m.
NEDg Description generation batch_69ffbf61b2ec81909c0f32613bb91a82 completed May 9, 2026, 11:12 p.m.
NED2 Entity disambiguation (via description) batch_69ffbfdfe58c8190b5964b6f5812ef65 completed May 9, 2026, 11:14 p.m.
Created at: April 10, 2026, 4:53 a.m.