Triple

T25031520
Position Surface form Disambiguated ID Type / Status
Subject Don Robey E626857 entity
Predicate birthName P65 FINISHED
Object Don Deadric Robey
Don Deadric Robey was an influential American music executive and entrepreneur best known for founding Peacock Records and shaping mid-20th-century rhythm and blues and gospel music.
E1661063 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: Don Deadric Robey | Statement: [Don Robey, birthName, Don Deadric Robey]
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: Don Deadric Robey
Triple: [Don Robey, birthName, Don Deadric Robey]
Generated description
Don Deadric Robey was an influential American music executive and entrepreneur best known for founding Peacock Records and shaping mid-20th-century rhythm and blues and gospel music.

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_69e2ff2a2c088190be513727ee8bfe78 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44f6fcab081909470c94a5f519d79 completed May 1, 2026, 7 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048bb7b088190b48ca45a4f6dfc2f completed May 22, 2026, 12:14 p.m.
NEDg Description generation batch_6a1049b63de881908e04b30b555d7809 completed May 22, 2026, 12:19 p.m.
NED2 Entity disambiguation (via description) batch_6a104a7bba188190b4d819ed6c618086 completed May 22, 2026, 12:22 p.m.
Created at: April 18, 2026, 6:07 a.m.