Triple

T21834331
Position Surface form Disambiguated ID Type / Status
Subject Papal conclave, 1724 E539078 entity
Predicate notableCardinalElector P145496 FINISHED
Object Nicolas de Bussières
Nicolas de Bussières was an 18th-century French cardinal of the Catholic Church who played a significant role in the papal conclave of 1724.
E1712753 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: Nicolas de Bussières | Statement: [Papal conclave, 1724, notableCardinalElector, Nicolas de Bussières]
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: Nicolas de Bussières
Triple: [Papal conclave, 1724, notableCardinalElector, Nicolas de Bussières]
Generated description
Nicolas de Bussières was an 18th-century French cardinal of the Catholic Church who played a significant role in the papal conclave of 1724.

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_69e0c475cda88190987d08f23caebdc1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0a7a6c9688190aa357377b4697a47 completed April 28, 2026, 12:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118532500c819090062bcd7f3eeb8f completed May 23, 2026, 10:45 a.m.
NEDg Description generation batch_6a1185c3841081909a717baf5f3a38fb completed May 23, 2026, 10:47 a.m.
NED2 Entity disambiguation (via description) batch_6a11864330048190a6b55f72fb7c89c1 completed May 23, 2026, 10:49 a.m.
Created at: April 16, 2026, 6:55 p.m.