Triple

T408024
Position Surface form Disambiguated ID Type / Status
Subject Massif Central E9424 entity
Predicate contains P35 FINISHED
Object Margeride
Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
 E52803 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: Margeride | Statement: [Massif Central, contains, Margeride]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Margeride
Context triple: [Massif Central, contains, Margeride]
  • A. Volnay
    Volnay is a renowned wine-producing village in Burgundy, France, celebrated for its elegant, aromatic red wines made primarily from Pinot Noir.
  • B. Dardagny
    Dardagny is a rural Swiss municipality known for its vineyards and scenic landscapes in the western part of the canton of Geneva.
  • C. Clémentine
    Clémentine is a feminine given name of French origin, commonly used in Francophone countries and beyond.
  • D. Pierrette
    Pierrette is a French feminine given name, traditionally considered the female form of Pierre.
  • E. Gamay
    Gamay is a red wine grape variety best known for producing light, fruity wines, particularly in France’s Beaujolais 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: Margeride
Triple: [Massif Central, contains, Margeride]
Generated description
Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Margeride
Target entity description: Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
  • A. Volnay
    Volnay is a renowned wine-producing village in Burgundy, France, celebrated for its elegant, aromatic red wines made primarily from Pinot Noir.
  • B. Dardagny
    Dardagny is a rural Swiss municipality known for its vineyards and scenic landscapes in the western part of the canton of Geneva.
  • C. Clémentine
    Clémentine is a feminine given name of French origin, commonly used in Francophone countries and beyond.
  • D. Pierrette
    Pierrette is a French feminine given name, traditionally considered the female form of Pierre.
  • E. Gamay
    Gamay is a red wine grape variety best known for producing light, fruity wines, particularly in France’s Beaujolais 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_69a2e80111fc8190961d5b7c6154123f completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ecbf0650819080753815ca280eec completed Feb. 28, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4239ffb5c819091b96dbe38a06d07 completed March 1, 2026, 11:31 a.m.
NEDg Description generation batch_69a423fc21188190bacc03bfae9ac401 completed March 1, 2026, 11:33 a.m.
NED2 Entity disambiguation (via description) batch_69a42486e1e08190b7603c34d625da7c completed March 1, 2026, 11:35 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.