Triple

T16617315
Position Surface form Disambiguated ID Type / Status
Subject Limousin Occitan E403727 entity
Predicate hasDialect P4251 FINISHED
Object Nontronnais
Nontronnais is a regional dialect of the Limousin variety of the Occitan language, traditionally spoken around the town of Nontron in southwestern France.
E1223871 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: Nontronnais | Statement: [Limousin Occitan, hasDialect, Nontronnais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nontronnais
Context triple: [Limousin Occitan, hasDialect, Nontronnais]
  • A. Verdunois
    Verdunois is a regional dialect of the Lorrain Romance language traditionally spoken around the area of Verdun in northeastern France.
  • B. Auberjonois
    Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
  • C. Ambertois
    Ambertois is the French demonym for inhabitants of the town of Ambert in central France.
  • D. Brionnais
    Brionnais is a historic rural region in eastern France known for its Romanesque churches, traditional stone villages, and Charolais cattle farming.
  • E. Nivernais
    Nivernais is a historic province in central France, centered around the town of Nevers and known for its rural landscapes and traditional agriculture.
  • 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: Nontronnais
Triple: [Limousin Occitan, hasDialect, Nontronnais]
Generated description
Nontronnais is a regional dialect of the Limousin variety of the Occitan language, traditionally spoken around the town of Nontron in southwestern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nontronnais
Target entity description: Nontronnais is a regional dialect of the Limousin variety of the Occitan language, traditionally spoken around the town of Nontron in southwestern France.
  • A. Verdunois
    Verdunois is a regional dialect of the Lorrain Romance language traditionally spoken around the area of Verdun in northeastern France.
  • B. Auberjonois
    Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
  • C. Ambertois
    Ambertois is the French demonym for inhabitants of the town of Ambert in central France.
  • D. Brionnais
    Brionnais is a historic rural region in eastern France known for its Romanesque churches, traditional stone villages, and Charolais cattle farming.
  • E. Nivernais
    Nivernais is a historic province in central France, centered around the town of Nevers and known for its rural landscapes and traditional agriculture.
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3754ac9dc8190965197024594742b completed April 18, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007daef18481908c3628a3466300ce completed May 10, 2026, 12:44 p.m.
NEDg Description generation batch_6a007e6507208190b3f32c05a2f647bd completed May 10, 2026, 12:47 p.m.
NED2 Entity disambiguation (via description) batch_6a007f2cefa081908734a907da33a72f completed May 10, 2026, 12:50 p.m.
Created at: April 10, 2026, 5:17 a.m.