Triple

T24125891
Position Surface form Disambiguated ID Type / Status
Subject Eugène de Mazenod E597799 entity
Predicate positionHeld P8 FINISHED
Object Vicar General of Marseille
The Vicar General of Marseille is a senior Catholic cleric who assists the Bishop of Marseille in governing the diocese and overseeing its pastoral and administrative affairs.
E1622391 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: Vicar General of Marseille | Statement: [Eugène de Mazenod, positionHeld, Vicar General of Marseille]
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: Vicar General of Marseille
Triple: [Eugène de Mazenod, positionHeld, Vicar General of Marseille]
Generated description
The Vicar General of Marseille is a senior Catholic cleric who assists the Bishop of Marseille in governing the diocese and overseeing its pastoral and administrative affairs.

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_69e288c808b881909fed7d18f04bcbbe completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1dee9086481909710c6d3291242c3 completed April 29, 2026, 10:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fad19ed148190941802509c24b5b2 completed May 22, 2026, 1:10 a.m.
NEDg Description generation batch_6a0fb121d0dc81909c74c152c17b5d56 completed May 22, 2026, 1:28 a.m.
NED2 Entity disambiguation (via description) batch_6a0fb1d7653c81909d8903f88d91a085 completed May 22, 2026, 1:31 a.m.
Created at: April 17, 2026, 11:06 p.m.