Triple

T32698635
Position Surface form Disambiguated ID Type / Status
Subject McAfee family E836079 entity
Predicate hasNotableMember P304 FINISHED
Object Kenyon McAfee
Kenyon McAfee is a notable member of the McAfee family, recognized for his prominence within that lineage.
E2029081 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: Kenyon McAfee | Statement: [McAfee family, hasNotableMember, Kenyon McAfee]
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: Kenyon McAfee
Triple: [McAfee family, hasNotableMember, Kenyon McAfee]
Generated description
Kenyon McAfee is a notable member of the McAfee family, recognized for his prominence within that lineage.

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_69f3493323288190a4e88251035fe96e completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c84b39a481908935e1ec690e566f completed May 3, 2026, 4 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34c664fa4481908004c8f5200d56ce completed June 19, 2026, 4:32 a.m.
NEDg Description generation batch_6a34ca32e1288190a271a3fc6f53a229 completed June 19, 2026, 4:48 a.m.
NED2 Entity disambiguation (via description) batch_6a34ca8816f081909c0106a86e72d5bb completed June 19, 2026, 4:50 a.m.
Created at: May 1, 2026, 1:10 a.m.