Triple

T23918362
Position Surface form Disambiguated ID Type / Status
Subject Abbot of Cluny E602141 entity
Predicate firstHolder P291 FINISHED
Object Bernon of Baume
Bernon of Baume was a 10th-century Benedictine monk and reformer who became the founding abbot of Cluny, helping launch one of medieval Europe’s most influential monastic movements.
E1609181 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: Bernon of Baume | Statement: [Abbot of Cluny, firstHolder, Bernon of Baume]
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: Bernon of Baume
Triple: [Abbot of Cluny, firstHolder, Bernon of Baume]
Generated description
Bernon of Baume was a 10th-century Benedictine monk and reformer who became the founding abbot of Cluny, helping launch one of medieval Europe’s most influential monastic movements.

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_69e2953a187081908346a9f36e85fc98 completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1cf1600248190b38cfc93afb22a73 completed April 29, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f763baea88190b70e978613e53fd0 completed May 21, 2026, 9:16 p.m.
NEDg Description generation batch_6a0f7721b65481908b58b4d68e50768c completed May 21, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0f788c4c108190b79e1ea898be2a80 completed May 21, 2026, 9:26 p.m.
Created at: April 17, 2026, 8:41 p.m.