Triple

T24703901
Position Surface form Disambiguated ID Type / Status
Subject Sir J. J. School of Art E611834 entity
Predicate founder P104 FINISHED
Object Sir Jamsetjee Jejeebhoy
Sir Jamsetjee Jejeebhoy was a prominent 19th-century Parsi merchant and philanthropist from Bombay, renowned for his extensive charitable endowments to education, healthcare, and public institutions across India.
 E1647620 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: Sir Jamsetjee Jejeebhoy | Statement: [Sir J. J. School of Art, founder, Sir Jamsetjee Jejeebhoy]
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: Sir Jamsetjee Jejeebhoy
Triple: [Sir J. J. School of Art, founder, Sir Jamsetjee Jejeebhoy]
Generated description
Sir Jamsetjee Jejeebhoy was a prominent 19th-century Parsi merchant and philanthropist from Bombay, renowned for his extensive charitable endowments to education, healthcare, and public institutions across India.

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_69e2c4d9c24c8190a3712d74327f0c6e completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40ff2474c819094f5bc2c9ce7e80b completed May 1, 2026, 2:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10100bfc2c8190a197cdea1521b910 completed May 22, 2026, 8:13 a.m.
NEDg Description generation batch_6a10136b70f4819096d05c3f3fed09c2 completed May 22, 2026, 8:27 a.m.
NED2 Entity disambiguation (via description) batch_6a10145c05c88190a29367197865506c completed May 22, 2026, 8:31 a.m.
Created at: April 18, 2026, 3:23 a.m.