Triple

T24659018
Position Surface form Disambiguated ID Type / Status
Subject Peschadoires E610483 entity
Predicate hasIntercommunality P15149 FINISHED
Object Entre Dore et Allier
Entre Dore et Allier is a French intercommunal structure in the Puy-de-Dôme department that groups several neighboring communes for cooperative local administration and services.
E1644075 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: Entre Dore et Allier | Statement: [Peschadoires, hasIntercommunality, Entre Dore et Allier]
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: Entre Dore et Allier
Triple: [Peschadoires, hasIntercommunality, Entre Dore et Allier]
Generated description
Entre Dore et Allier is a French intercommunal structure in the Puy-de-Dôme department that groups several neighboring communes for cooperative local administration and services.

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_69e2c4d453248190a020354e93ef6282 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40f96ea888190a995da1a57e1e68f completed May 1, 2026, 2:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10049e62b48190a0e9cf4c0c8130c2 completed May 22, 2026, 7:24 a.m.
NEDg Description generation batch_6a100640e64081909c54d3a2761007fb completed May 22, 2026, 7:31 a.m.
NED2 Entity disambiguation (via description) batch_6a1006c065cc81908af8ae63739b4c37 completed May 22, 2026, 7:33 a.m.
Created at: April 18, 2026, 2:34 a.m.