Triple

T25705905
Position Surface form Disambiguated ID Type / Status
Subject Cannons, the estate of James Brydges, Duke of Chandos E644587 entity
Predicate patron P2320 FINISHED
Object Antonio Bellucci
Antonio Bellucci was an Italian Baroque painter known for his grand decorative and religious works in churches and aristocratic residences across Europe, including England and Austria.
E1971932 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: Antonio Bellucci | Statement: [Cannons, the estate of James Brydges, Duke of Chandos, patron, Antonio Bellucci]
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: Antonio Bellucci
Triple: [Cannons, the estate of James Brydges, Duke of Chandos, patron, Antonio Bellucci]
Generated description
Antonio Bellucci was an Italian Baroque painter known for his grand decorative and religious works in churches and aristocratic residences across Europe, including England and Austria.

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_69e77e83c8ec8190bf52fcdac4838984 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fc113b40819088a0d53c824097e4 completed May 2, 2026, 1:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2b79a5badc8190bbb878f181664757 completed June 12, 2026, 3:14 a.m.
NEDg Description generation batch_6a2b7a866a408190a377ebe1dfb4b162 completed June 12, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a2b7b5699c48190b83c080aa685a7b4 completed June 12, 2026, 3:21 a.m.
Created at: April 21, 2026, 9:04 p.m.