Triple

T34755677
Position Surface form Disambiguated ID Type / Status
Subject Aissa Wayne E1001913 entity
Predicate notableWork P4 FINISHED
Object John Wayne: My Father
"John Wayne: My Father" is a biographical memoir in which Aissa Wayne recounts the life, career, and personal side of her father, iconic Hollywood actor John Wayne.
 E2111540 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: John Wayne: My Father | Statement: [Aissa Wayne, notableWork, John Wayne: My Father]
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: John Wayne: My Father
Triple: [Aissa Wayne, notableWork, John Wayne: My Father]
Generated description
"John Wayne: My Father" is a biographical memoir in which Aissa Wayne recounts the life, career, and personal side of her father, iconic Hollywood actor John Wayne.

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_69f76db0fb30819096709d43f9a1f45f completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f779efa8a88190a2a7a428813f9c55 completed May 3, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37663037e481908f31588458b55800 completed June 21, 2026, 4:18 a.m.
NEDg Description generation batch_6a3768cd30a48190a11841ed9010278c completed June 21, 2026, 4:30 a.m.
NED2 Entity disambiguation (via description) batch_6a376943e3108190904c01d27e73c367 completed June 21, 2026, 4:32 a.m.
Created at: May 3, 2026, 3:59 p.m.