Triple

T30817041
Position Surface form Disambiguated ID Type / Status
Subject Brucheville E784807 entity
Predicate governedBy P46 FINISHED
Object municipal council of Brucheville
The municipal council of Brucheville is the local governing body responsible for administering public affairs and making policy decisions for the commune of Brucheville in France.
E1933494 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: municipal council of Brucheville | Statement: [Brucheville, governedBy, municipal council of Brucheville]
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: municipal council of Brucheville
Triple: [Brucheville, governedBy, municipal council of Brucheville]
Generated description
The municipal council of Brucheville is the local governing body responsible for administering public affairs and making policy decisions for the commune of Brucheville in France.

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_69f224b4eda48190bd212ce4f3901e56 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6906994e88190a2da183455bdf076 completed May 3, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28bbe382f48190a8c72ee7c316188c completed June 10, 2026, 1:20 a.m.
NEDg Description generation batch_6a28bcce7b7c8190b7694f87ed55a5c8 completed June 10, 2026, 1:24 a.m.
NED2 Entity disambiguation (via description) batch_6a28bd9d23e48190bcd8bcf57d7d72e8 completed June 10, 2026, 1:27 a.m.
Created at: April 29, 2026, 8:44 p.m.