Triple

T4109022
Position Surface form Disambiguated ID Type / Status
Subject TGV Réseau E88522 entity
Predicate operatorClassDesignation P974 FINISHED
Object TGV R
TGV R is a class of French high-speed TGV Réseau trainsets used for long-distance passenger services on the national high-speed rail network.
 E445692 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 R | Statement: [TGV Réseau, operatorClassDesignation, TGV R]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TGV R
Context triple: [TGV Réseau, operatorClassDesignation, TGV R]
  • A. TGV PSE
    TGV PSE is the original generation of French high-speed TGV Sud-Est trainsets that inaugurated high-speed rail service in France.
  • B. TGV Est
    TGV Est is a French high-speed train service connecting Paris with eastern France and neighboring European countries such as Germany, Luxembourg, and Switzerland.
  • C. TGV Ouigo
    TGV Ouigo is a low-cost high-speed train service operated by SNCF in France, offering budget fares on selected TGV routes.
  • 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 and amenities on major routes including those served by the LGV Méditerranée line.
  • 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 R
Triple: [TGV Réseau, operatorClassDesignation, TGV R]
Generated description
TGV R is a class of French high-speed TGV Réseau trainsets used for long-distance passenger services on the national high-speed rail network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TGV R
Target entity description: TGV R is a class of French high-speed TGV Réseau trainsets used for long-distance passenger services on the national high-speed rail network.
  • A. TGV PSE
    TGV PSE is the original generation of French high-speed TGV Sud-Est trainsets that inaugurated high-speed rail service in France.
  • B. TGV Est
    TGV Est is a French high-speed train service connecting Paris with eastern France and neighboring European countries such as Germany, Luxembourg, and Switzerland.
  • C. TGV Ouigo
    TGV Ouigo is a low-cost high-speed train service operated by SNCF in France, offering budget fares on selected TGV routes.
  • 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 and amenities on major routes including those served by the LGV Méditerranée line.
  • 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_69aed9484fb881909146f4c772ad277c completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af01da2b88819088a45401c0ec743a completed March 9, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bb809c4c6c8190abeb7a5bad4fab67 completed March 19, 2026, 4:50 a.m.
NEDg Description generation batch_69bb821299448190905e9de00b04e943 completed March 19, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_69bb827d3e788190b65f54a12b4ed354 completed March 19, 2026, 4:58 a.m.
Created at: March 9, 2026, 3:40 p.m.