Triple

T35847036
Position Surface form Disambiguated ID Type / Status
Subject California Love E1036240 entity
Predicate writer P1360 FINISHED
Object Clarence Satchell
Clarence Satchell was an American saxophonist, songwriter, and member of the Ohio Players whose work has been widely sampled in hip-hop, including in the hit song "California Love."
E2159707 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: Clarence Satchell | Statement: [California Love, writer, Clarence Satchell]
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: Clarence Satchell
Triple: [California Love, writer, Clarence Satchell]
Generated description
Clarence Satchell was an American saxophonist, songwriter, and member of the Ohio Players whose work has been widely sampled in hip-hop, including in the hit song "California Love."

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_69f76e1a29e8819088280f26096aeb55 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a94dd1a48190bfc504909e806144 completed May 3, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38a4e287d88190ac8b9d809df193e7 completed June 22, 2026, 2:58 a.m.
NEDg Description generation batch_6a38a623d1cc8190851c5e67962db5f4 completed June 22, 2026, 3:04 a.m.
NED2 Entity disambiguation (via description) batch_6a38a6bafeb081908a73e8735069d039 completed June 22, 2026, 3:06 a.m.
Created at: May 3, 2026, 4:06 p.m.