Triple

T34517369
Position Surface form Disambiguated ID Type / Status
Subject Jean Mabillon E886187 entity
Predicate notableWork P4 FINISHED
Object Annales Ordinis Sancti Benedicti
Annales Ordinis Sancti Benedicti is a monumental multi-volume scholarly history of the Benedictine Order, authored by the French Maurist monk and historian Jean Mabillon.
E2103159 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: Annales Ordinis Sancti Benedicti | Statement: [Jean Mabillon, notableWork, Annales Ordinis Sancti Benedicti]
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: Annales Ordinis Sancti Benedicti
Triple: [Jean Mabillon, notableWork, Annales Ordinis Sancti Benedicti]
Generated description
Annales Ordinis Sancti Benedicti is a monumental multi-volume scholarly history of the Benedictine Order, authored by the French Maurist monk and historian Jean Mabillon.

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_69f349ccc290819089d8e82698e53cb6 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71f95ca408190b438f6444832dade completed May 3, 2026, 10:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a373617ec4c81909db6645e5383eb8a completed June 21, 2026, 12:53 a.m.
NEDg Description generation batch_6a3737d63c80819089c56c0637912612 completed June 21, 2026, 1:01 a.m.
NED2 Entity disambiguation (via description) batch_6a37389b73688190a878dc3e41d17b26 completed June 21, 2026, 1:04 a.m.
Created at: May 1, 2026, 2:01 a.m.