Triple

T5524143
Position Surface form Disambiguated ID Type / Status
Subject Montbrison E144882 entity
Predicate hasDemonym P191 FINISHED
Object Montbrisonnaise
Montbrisonnaise is the French term for a female inhabitant or native of the town of Montbrison in central France.
 E528560 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: Montbrisonnaise | Statement: [Montbrison, hasDemonym, Montbrisonnaise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Montbrisonnaise
Context triple: [Montbrison, hasDemonym, Montbrisonnaise]
  • A. Mont-Saint-André
    Mont-Saint-André is a village in Wallonia, Belgium, forming one of the districts of the municipality of Ramillies in the province of Walloon Brabant.
  • B. Mont-Dore
    Mont-Dore is a spa and ski resort town in central France’s Massif Central, known for its thermal springs and access to the nearby volcanic landscapes.
  • C. Mont-Dore
    Mont-Dore is a coastal commune and suburb of Nouméa in New Caledonia, known for its mountainous landscapes and residential areas.
  • D. Clessé
    Clessé is a wine-producing village in the Mâconnais region of Burgundy, France, known for its quality white wines.
  • E. Chamrousse
    Chamrousse is a French alpine ski resort and mountain commune in the Alps, known for its winter sports facilities and scenic high-altitude landscapes.
  • 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: Montbrisonnaise
Triple: [Montbrison, hasDemonym, Montbrisonnaise]
Generated description
Montbrisonnaise is the French term for a female inhabitant or native of the town of Montbrison in central France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Montbrisonnaise
Target entity description: Montbrisonnaise is the French term for a female inhabitant or native of the town of Montbrison in central France.
  • A. Mont-Saint-André
    Mont-Saint-André is a village in Wallonia, Belgium, forming one of the districts of the municipality of Ramillies in the province of Walloon Brabant.
  • B. Mont-Dore
    Mont-Dore is a spa and ski resort town in central France’s Massif Central, known for its thermal springs and access to the nearby volcanic landscapes.
  • C. Mont-Dore
    Mont-Dore is a coastal commune and suburb of Nouméa in New Caledonia, known for its mountainous landscapes and residential areas.
  • D. Clessé
    Clessé is a wine-producing village in the Mâconnais region of Burgundy, France, known for its quality white wines.
  • E. Chamrousse
    Chamrousse is a French alpine ski resort and mountain commune in the Alps, known for its winter sports facilities and scenic high-altitude landscapes.
  • 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_69c008f873a481909b4d9f7e2db3c37d completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f85c8508190a0a089402b49a04f completed March 22, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027f6aa1c8190b639c317c7d60f64 completed March 22, 2026, 5:33 p.m.
NEDg Description generation batch_69c033dc91e08190888fb6e94027fbdb completed March 22, 2026, 6:24 p.m.
NED2 Entity disambiguation (via description) batch_69c03460b21481908b78aa4bdc989d2c completed March 22, 2026, 6:26 p.m.
Created at: March 22, 2026, 3:34 p.m.