Triple

T31696387
Position Surface form Disambiguated ID Type / Status
Subject Edgar M. Bronfman Sr. E808928 entity
Predicate child P120 FINISHED
Object Matthew Bronfman
Matthew Bronfman is an American businessman, investor, and philanthropist known for his leadership in private equity and his prominent role in Jewish communal and educational organizations.
E1984456 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: Matthew Bronfman | Statement: [Edgar M. Bronfman Sr., child, Matthew Bronfman]
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: Matthew Bronfman
Triple: [Edgar M. Bronfman Sr., child, Matthew Bronfman]
Generated description
Matthew Bronfman is an American businessman, investor, and philanthropist known for his leadership in private equity and his prominent role in Jewish communal and educational organizations.

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_69f348de914081909fc8edff56f34dbe completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6aaa53a3881908f76b84f26c8577f completed May 3, 2026, 1:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e8a1925788190b93fd88116391842 completed June 14, 2026, 11:01 a.m.
NEDg Description generation batch_6a2e8aba8d9481908df3439168b0f62f completed June 14, 2026, 11:04 a.m.
NED2 Entity disambiguation (via description) batch_6a2e8b6f6f2c819098e1787c61964edd completed June 14, 2026, 11:07 a.m.
Created at: April 30, 2026, 11:10 p.m.