Triple

T10541124
Position Surface form Disambiguated ID Type / Status
Subject TGV Ouigo E248696 entity
Predicate notableRoute P22 FINISHED
Object Paris–Montpellier
Paris–Montpellier is a major high-speed rail corridor in France linking the capital with the Mediterranean city of Montpellier.
 E871013 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: Paris–Montpellier | Statement: [TGV Ouigo, notableRoute, Paris–Montpellier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paris–Montpellier
Context triple: [TGV Ouigo, notableRoute, Paris–Montpellier]
  • A. Bordeaux–Toulouse–Marseille
    Bordeaux–Toulouse–Marseille is a major French intercity rail corridor linking the Atlantic city of Bordeaux with Toulouse and the Mediterranean port of Marseille.
  • B. Paris–Strasbourg
    Paris–Strasbourg is a major high-speed rail corridor in France linking the capital with the Alsatian city near the German border.
  • C. Paris–Toulouse
    Paris–Toulouse is a major intercity rail corridor in France linking the capital Paris with the southwestern city of Toulouse.
  • D. Paris–Marseille
    Paris–Marseille is a major French intercity rail corridor linking the capital Paris with the Mediterranean port city of Marseille.
  • E. Montpellier
    Montpellier is a major city in southern France known for its medieval old town, vibrant university life, and proximity to the Mediterranean coast.
  • 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: Paris–Montpellier
Triple: [TGV Ouigo, notableRoute, Paris–Montpellier]
Generated description
Paris–Montpellier is a major high-speed rail corridor in France linking the capital with the Mediterranean city of Montpellier.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paris–Montpellier
Target entity description: Paris–Montpellier is a major high-speed rail corridor in France linking the capital with the Mediterranean city of Montpellier.
  • A. Bordeaux–Toulouse–Marseille
    Bordeaux–Toulouse–Marseille is a major French intercity rail corridor linking the Atlantic city of Bordeaux with Toulouse and the Mediterranean port of Marseille.
  • B. Paris–Strasbourg
    Paris–Strasbourg is a major high-speed rail corridor in France linking the capital with the Alsatian city near the German border.
  • C. Paris–Toulouse
    Paris–Toulouse is a major intercity rail corridor in France linking the capital Paris with the southwestern city of Toulouse.
  • D. Paris–Marseille
    Paris–Marseille is a major French intercity rail corridor linking the capital Paris with the Mediterranean port city of Marseille.
  • E. Montpellier
    Montpellier is a major city in southern France known for its medieval old town, vibrant university life, and proximity to the Mediterranean coast.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d50a5918648190b16c2d1bc1bf015f completed April 7, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9341d96c08190a6ba644b9acfe2c8 completed April 10, 2026, 5:32 p.m.
NEDg Description generation batch_69d93802a4488190aa86ae209650d4e7 completed April 10, 2026, 5:48 p.m.
NED2 Entity disambiguation (via description) batch_69d938fcc3c48190a4acaaf75c1aa304 completed April 10, 2026, 5:53 p.m.
Created at: April 6, 2026, 12:32 p.m.