Triple

T26360338
Position Surface form Disambiguated ID Type / Status
Subject Redemption: The Stan Tookie Williams Story E660183 entity
Predicate mainSubject P3 FINISHED
Object Stanley "Tookie" Williams
Stanley "Tookie" Williams was a co-founder of the Crips street gang who later became an anti-gang activist and Nobel Peace Prize nominee while on death row.
E1721484 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: Stanley "Tookie" Williams | Statement: [Redemption: The Stan Tookie Williams Story, mainSubject, Stanley "Tookie" Williams]
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: Stanley "Tookie" Williams
Triple: [Redemption: The Stan Tookie Williams Story, mainSubject, Stanley "Tookie" Williams]
Generated description
Stanley "Tookie" Williams was a co-founder of the Crips street gang who later became an anti-gang activist and Nobel Peace Prize nominee while on death row.

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_69ee8126d52c8190bc0b34337c2c9aa8 completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f60ff2f3f48190bd89e2d9ec8e56f7 completed May 2, 2026, 2:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a119a6bed8081909ea937e062d9c5e3 completed May 23, 2026, 12:15 p.m.
NEDg Description generation batch_6a119b150b7c81909265302179aef83e completed May 23, 2026, 12:18 p.m.
NED2 Entity disambiguation (via description) batch_6a119c7d5eac8190ae6fbb97bf64b472 completed May 23, 2026, 12:24 p.m.
Created at: April 26, 2026, 10:51 p.m.