Triple

T38547914
Position Surface form Disambiguated ID Type / Status
Subject Poppy Delevingne E925021 entity
Predicate parent P120 FINISHED
Object Pandora Delevingne
Pandora Delevingne is a British socialite and personal shopper, best known as the mother of models Poppy and Cara Delevingne and a member of the prominent Delevingne family.
E2281902 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: Pandora Delevingne | Statement: [Poppy Delevingne, parent, Pandora Delevingne]
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: Pandora Delevingne
Triple: [Poppy Delevingne, parent, Pandora Delevingne]
Generated description
Pandora Delevingne is a British socialite and personal shopper, best known as the mother of models Poppy and Cara Delevingne and a member of the prominent Delevingne family.

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_69f76eaeb69c8190b367df9330d6f6af completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd313e61c8190b174b331365b803f completed May 7, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a420dfb340c8190b78b2672f3f1bc6b completed June 29, 2026, 6:17 a.m.
NEDg Description generation batch_6a420ea4e7ec819099129255779eeca8 completed June 29, 2026, 6:20 a.m.
NED2 Entity disambiguation (via description) batch_6a420f1638208190b44dd11ddf37c474 completed June 29, 2026, 6:22 a.m.
Created at: May 3, 2026, 4:32 p.m.