Triple

T32698660
Position Surface form Disambiguated ID Type / Status
Subject McAfee family E836079 entity
Predicate hasNotableMember P304 FINISHED
Object Margaret McAfee
Margaret McAfee is a notable member of the McAfee family, recognized for her significance within this prominent lineage.
E2143713 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: Margaret McAfee | Statement: [McAfee family, hasNotableMember, Margaret 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: Margaret McAfee
Triple: [McAfee family, hasNotableMember, Margaret McAfee]
Generated description
Margaret McAfee is a notable member of the McAfee family, recognized for her significance within this prominent 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_6a384a11f5f08190b635329a29b1284b completed June 21, 2026, 8:31 p.m.
NEDg Description generation batch_6a384ad781b48190b37e3ae4708eae57 completed June 21, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_6a384b6644208190b1c18024a063846b completed June 21, 2026, 8:36 p.m.
Created at: May 1, 2026, 1:10 a.m.