Triple

T23737828
Position Surface form Disambiguated ID Type / Status
Subject Whitmore E586583 entity
Predicate hasNotableFamily P3600 FINISHED
Object Whitmore family of Staffordshire
The Whitmore family of Staffordshire is an English gentry lineage historically associated with landownership, local influence, and public service in Staffordshire.
E1598530 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: Whitmore family of Staffordshire | Statement: [Whitmore, hasNotableFamily, Whitmore family of Staffordshire]
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: Whitmore family of Staffordshire
Triple: [Whitmore, hasNotableFamily, Whitmore family of Staffordshire]
Generated description
The Whitmore family of Staffordshire is an English gentry lineage historically associated with landownership, local influence, and public service in Staffordshire.

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_69e24907dc9c8190be074c9c96a0ec2d completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1bad356c88190ae29ce403145ee73 completed April 29, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f53c99460819089e3714dbcf952ba completed May 21, 2026, 6:49 p.m.
NEDg Description generation batch_6a0f559912b48190b5b826baf86c25b4 completed May 21, 2026, 6:57 p.m.
NED2 Entity disambiguation (via description) batch_6a0f5608ad688190ba10298e21c600e7 completed May 21, 2026, 6:59 p.m.
Created at: April 17, 2026, 7:11 p.m.