Triple

T29984431
Position Surface form Disambiguated ID Type / Status
Subject Villa di Poggio Imperiale E761689 entity
Predicate architect P184 FINISHED
Object Gaspare Maria Paoletti
Gaspare Maria Paoletti was an 18th-century Italian architect known for his neoclassical designs and significant contributions to the architecture of Tuscany.
E2297466 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: Gaspare Maria Paoletti | Statement: [Villa di Poggio Imperiale, architect, Gaspare Maria Paoletti]
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: Gaspare Maria Paoletti
Triple: [Villa di Poggio Imperiale, architect, Gaspare Maria Paoletti]
Generated description
Gaspare Maria Paoletti was an 18th-century Italian architect known for his neoclassical designs and significant contributions to the architecture of Tuscany.

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_69f2246851148190b8e76206db94b105 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f678dc12c481909e88cb5cf37d5d29 completed May 2, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a83876383dc8190aaf8a3199b5d8aaa completed Aug. 17, 2026, 10:12 p.m.
NEDg Description generation batch_6a8387ccab888190ad02e59c0ba70f1d completed Aug. 17, 2026, 10:14 p.m.
NED2 Entity disambiguation (via description) batch_6a838825cb2481909789a61ff556b5b4 completed Aug. 17, 2026, 10:16 p.m.
Created at: April 29, 2026, 6:36 p.m.