Triple

T929735
Position Surface form Disambiguated ID Type / Status
Subject Franco-Provençal E20062 entity
Predicate hasDialects P4251 FINISHED
Object Cellese
Cellese is a regional dialect of the Franco-Provençal language traditionally spoken in a specific area of the Franco-Provençal linguistic region.
 E112018 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: Cellese | Statement: [Franco-Provençal, hasDialects, Cellese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cellese
Context triple: [Franco-Provençal, hasDialects, Cellese]
  • A. Celle
    Celle is a historic town in northern Germany renowned for its well-preserved half-timbered old town and ducal palace.
  • B. Ascella
    Ascella is a prominent multiple star system in the constellation Sagittarius, known for being one of its brightest and most easily visible stars.
  • C. Barellan
    Barellan is a small rural town in the Riverina region of New South Wales, Australia, known for its grain farming and association with tennis champion Evonne Goolagong-Cawley.
  • D. Lozanella
    Lozanella is a small genus of flowering plants in the hemp family Cannabaceae, native to parts of Central and South America.
  • E. Soral
    Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
  • 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: Cellese
Triple: [Franco-Provençal, hasDialects, Cellese]
Generated description
Cellese is a regional dialect of the Franco-Provençal language traditionally spoken in a specific area of the Franco-Provençal linguistic region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cellese
Target entity description: Cellese is a regional dialect of the Franco-Provençal language traditionally spoken in a specific area of the Franco-Provençal linguistic region.
  • A. Celle
    Celle is a historic town in northern Germany renowned for its well-preserved half-timbered old town and ducal palace.
  • B. Ascella
    Ascella is a prominent multiple star system in the constellation Sagittarius, known for being one of its brightest and most easily visible stars.
  • C. Barellan
    Barellan is a small rural town in the Riverina region of New South Wales, Australia, known for its grain farming and association with tennis champion Evonne Goolagong-Cawley.
  • D. Lozanella
    Lozanella is a small genus of flowering plants in the hemp family Cannabaceae, native to parts of Central and South America.
  • E. Soral
    Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
  • 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_69a493af3dc48190adb7263e6e445ea1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b349b3d0819090c58b4fb60c6a1b completed March 1, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a933a103908190a624039492079f82 completed March 5, 2026, 7:41 a.m.
NEDg Description generation batch_69a94d60cb3c81908dc3af7bc395505f completed March 5, 2026, 9:31 a.m.
NED2 Entity disambiguation (via description) batch_69a963c897888190bec5decc6010c9d6 completed March 5, 2026, 11:06 a.m.
Created at: March 1, 2026, 7:40 p.m.