Triple

T32443281
Position Surface form Disambiguated ID Type / Status
Subject Dessel E829070 entity
Predicate governedBy P46 FINISHED
Object municipal council of Dessel
The municipal council of Dessel is the local elected governing body responsible for setting policies, budgets, and regulations for the municipality of Dessel in Belgium.
E2006903 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 Dessel | Statement: [Dessel, governedBy, municipal council of Dessel]
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 Dessel
Triple: [Dessel, governedBy, municipal council of Dessel]
Generated description
The municipal council of Dessel is the local elected governing body responsible for setting policies, budgets, and regulations for the municipality of Dessel in Belgium.

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_69f3491d2e5c819092b1c9535beff8ec completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c2e3d0108190bd5ecee75e662368 completed May 3, 2026, 3:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a344f37f23081908983f9c745f3ab55 completed June 18, 2026, 8:04 p.m.
NEDg Description generation batch_6a345212a1c48190ac58fa101c175135 completed June 18, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_6a345f7387508190853808812475575f completed June 18, 2026, 9:13 p.m.
Created at: May 1, 2026, 12:55 a.m.