Triple

T36439449
Position Surface form Disambiguated ID Type / Status
Subject Roman Catholic Diocese of Gonaïves E897686 entity
Predicate previousBishop P59715 FINISHED
Object Jean-Marie Guillaume
Jean-Marie Guillaume is a Haitian Roman Catholic prelate who formerly served as the bishop of the Diocese of Gonaïves.
E2297423 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: Jean-Marie Guillaume | Statement: [Roman Catholic Diocese of Gonaïves, previousBishop, Jean-Marie Guillaume]
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: Jean-Marie Guillaume
Triple: [Roman Catholic Diocese of Gonaïves, previousBishop, Jean-Marie Guillaume]
Generated description
Jean-Marie Guillaume is a Haitian Roman Catholic prelate who formerly served as the bishop of the Diocese of Gonaïves.

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_69f76e56636481908eda808ab0273401 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd6cd59c8190a18122dca3373f67 completed May 3, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a837e5f418c8190a5c4a45a2101baa7 completed Aug. 17, 2026, 9:34 p.m.
NEDg Description generation batch_6a837ed03fac81908608f1560545707d completed Aug. 17, 2026, 9:36 p.m.
NED2 Entity disambiguation (via description) batch_6a837f211d5081909cd564bc92de540e completed Aug. 17, 2026, 9:37 p.m.
Created at: May 3, 2026, 4:10 p.m.