Triple

T16566073
Position Surface form Disambiguated ID Type / Status
Subject Gare de Lorraine TGV E402462 entity
Predicate locatedNear P294 FINISHED
Object Louvigny
Louvigny is a small commune in northeastern France known for its proximity to the high-speed Lorraine TGV railway station.
E1280813 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: Louvigny | Statement: [Gare de Lorraine TGV, locatedNear, Louvigny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louvigny
Context triple: [Gare de Lorraine TGV, locatedNear, Louvigny]
  • A. Juvigny
    Juvigny is a small French commune located in the Haute-Savoie department in the Auvergne-Rhône-Alpes region of southeastern France.
  • B. Vernouillet
    Vernouillet is a commune in northern France located in the Eure-et-Loir department in the Centre-Val de Loire region.
  • C. Bovigny
    Bovigny is a village in the municipality of Gouvy in the province of Luxembourg, Belgium.
  • D. Remigny
    Remigny is a small wine-producing village in the Burgundy region of eastern France, situated near the renowned appellation of Santenay.
  • E. Chauvigny
    Chauvigny is a historic town in western France known for its medieval fortifications and picturesque setting in the Vienne department of the Nouvelle-Aquitaine region.
  • 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: Louvigny
Triple: [Gare de Lorraine TGV, locatedNear, Louvigny]
Generated description
Louvigny is a small commune in northeastern France known for its proximity to the high-speed Lorraine TGV railway station.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Louvigny
Target entity description: Louvigny is a small commune in northeastern France known for its proximity to the high-speed Lorraine TGV railway station.
  • A. Juvigny
    Juvigny is a small French commune located in the Haute-Savoie department in the Auvergne-Rhône-Alpes region of southeastern France.
  • B. Vernouillet
    Vernouillet is a commune in northern France located in the Eure-et-Loir department in the Centre-Val de Loire region.
  • C. Bovigny
    Bovigny is a village in the municipality of Gouvy in the province of Luxembourg, Belgium.
  • D. Remigny
    Remigny is a small wine-producing village in the Burgundy region of eastern France, situated near the renowned appellation of Santenay.
  • E. Chauvigny
    Chauvigny is a historic town in western France known for its medieval fortifications and picturesque setting in the Vienne department of the Nouvelle-Aquitaine region.
  • 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35772255881909f737da89bcd06b8 completed April 18, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a021633fc848190b33798dc10ca0d55 completed May 11, 2026, 5:47 p.m.
NEDg Description generation batch_6a0218494d0c819096fa32b39524f960 completed May 11, 2026, 5:56 p.m.
NED2 Entity disambiguation (via description) batch_6a0218abde2c81908b6fec30ef40876f completed May 11, 2026, 5:58 p.m.
Created at: April 10, 2026, 5:15 a.m.