Triple

T35663068
Position Surface form Disambiguated ID Type / Status
Subject Miles Ahead E1030488 entity
Predicate starredActor P5563 FINISHED
Object Keith Stanfield
Keith Stanfield is an American actor and musician known for his versatile performances in films like "Short Term 12," "Get Out," and "Sorry to Bother You," as well as the TV series "Atlanta."
E2153360 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: Keith Stanfield | Statement: [Miles Ahead, starredActor, Keith Stanfield]
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: Keith Stanfield
Triple: [Miles Ahead, starredActor, Keith Stanfield]
Generated description
Keith Stanfield is an American actor and musician known for his versatile performances in films like "Short Term 12," "Get Out," and "Sorry to Bother You," as well as the TV series "Atlanta."

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_69f76e09f87881909c954aaac176c34f completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79fa913c48190a609dfd9c184afbc completed May 3, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a387d02ce5c8190a3d391bc9a244cc7 completed June 22, 2026, 12:08 a.m.
NEDg Description generation batch_6a3880c9de90819095648056040c9e9d completed June 22, 2026, 12:24 a.m.
NED2 Entity disambiguation (via description) batch_6a388122a1788190aa7017c270a95816 completed June 22, 2026, 12:26 a.m.
Created at: May 3, 2026, 4:05 p.m.