Triple

T8306552
Position Surface form Disambiguated ID Type / Status
Subject Hennebont E194476 entity
Predicate hasDemonym P191 FINISHED
Object Hennebontais
Hennebontais are the inhabitants or natives of Hennebont, a historic town in the Morbihan department of Brittany in northwestern France.
 E194476 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: Hennebontais | Statement: [Hennebont, hasDemonym, Hennebontais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hennebontais
Context triple: [Hennebont, hasDemonym, Hennebontais]
  • A. Hennebont
    Hennebont is a historic town in the Morbihan department of Brittany in northwestern France, known for its medieval ramparts and cultural heritage.
  • 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. Breuillet
    Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
  • D. Haubourdin
    Haubourdin is a commune in northern France, located near Lille in the Nord department of the Hauts-de-France region.
  • E. Tatihou
    Tatihou is a small French island off the coast of Normandy known for its historic Vauban fortifications, maritime museum, and rich coastal birdlife.
  • 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: Hennebontais
Triple: [Hennebont, hasDemonym, Hennebontais]
Generated description
Hennebontais are the inhabitants or natives of Hennebont, a historic town in the Morbihan department of Brittany in northwestern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hennebontais
Target entity description: Hennebontais are the inhabitants or natives of Hennebont, a historic town in the Morbihan department of Brittany in northwestern France.
  • A. Hennebont chosen
    Hennebont is a historic town in the Morbihan department of Brittany in northwestern France, known for its medieval ramparts and cultural heritage.
  • 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. Breuillet
    Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
  • D. Haubourdin
    Haubourdin is a commune in northern France, located near Lille in the Nord department of the Hauts-de-France region.
  • E. Tatihou
    Tatihou is a small French island off the coast of Normandy known for its historic Vauban fortifications, maritime museum, and rich coastal birdlife.
  • F. None of above.

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_69ca82e613e88190bf8139669bbd0d53 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f293db08190912e5e8bb7e940cf completed March 31, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd955100448190862fd52d660585fd completed April 1, 2026, 9:59 p.m.
NEDg Description generation batch_69cda342c10881908ebafc7853815424 completed April 1, 2026, 10:59 p.m.
NED2 Entity disambiguation (via description) batch_69cdab736f208190a90bd4344b21a22c completed April 1, 2026, 11:34 p.m.
Created at: March 30, 2026, 5:54 p.m.