Triple

T36166956
Position Surface form Disambiguated ID Type / Status
Subject Georgette Lizette Withers E1046030 entity
Predicate familyName P18 FINISHED
Object Withers
Withers is an English surname borne by various notable individuals across fields such as acting, music, and photography.
E1307870 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: Withers | Statement: [Georgette Lizette Withers, familyName, Withers]
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: Withers
Triple: [Georgette Lizette Withers, familyName, Withers]
Generated description
Withers is an English surname borne by various notable individuals across fields such as acting, music, and photography.

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_69f76e396bc88190b99d221bff9be27a completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b4f1971c81909442f664538a9f54 completed May 3, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a390d58f0f081908d047f31ef90ce34 completed June 22, 2026, 10:24 a.m.
NEDg Description generation batch_6a390e510fc8819084f001406a3a1ffe completed June 22, 2026, 10:28 a.m.
NED2 Entity disambiguation (via description) batch_6a390f2ec2c08190806b511afdefa6f1 completed June 22, 2026, 10:32 a.m.
Created at: May 3, 2026, 4:08 p.m.