Triple

T26331231
Position Surface form Disambiguated ID Type / Status
Subject arrondissement of Dole E662389 entity
Predicate category P87 FINISHED
Object Arrondissements of Jura department
The Arrondissements of Jura department are the administrative subdivisions of France’s Jura department, each grouping several communes for local governance and state administration.
E1719364 NE FINISHED

How this triple was built (2 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: Arrondissements of Jura department | Statement: [arrondissement of Dole, category, Arrondissements of Jura department]
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: Arrondissements of Jura department
Triple: [arrondissement of Dole, category, Arrondissements of Jura department]
Generated description
The Arrondissements of Jura department are the administrative subdivisions of France’s Jura department, each grouping several communes for local governance and state administration.

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_69ee812f32748190871d970c4e2a8ddf completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f60f692278819097b2c2470a88a43a completed May 2, 2026, 2:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118fe0ff308190a97051012a6aead2 completed May 23, 2026, 11:30 a.m.
NEDg Description generation batch_6a119405585c81909fcdac815503cb52 completed May 23, 2026, 11:48 a.m.
NED2 Entity disambiguation (via description) batch_6a11946a8d308190be5eba38199a037f completed May 23, 2026, 11:50 a.m.
Created at: April 26, 2026, 10:33 p.m.