Triple

T26078859
Position Surface form Disambiguated ID Type / Status
Subject Dancing with the Stars (season 31) E657770 entity
Predicate winner P354 FINISHED
Object Charli D'Amelio
Charli D'Amelio is an American social media personality and dancer who rose to fame on TikTok for her viral dance videos and has since expanded into television, brand partnerships, and other entertainment ventures.
E1714535 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: Charli D'Amelio | Statement: [Dancing with the Stars (season 31), winner, Charli D'Amelio]
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: Charli D'Amelio
Triple: [Dancing with the Stars (season 31), winner, Charli D'Amelio]
Generated description
Charli D'Amelio is an American social media personality and dancer who rose to fame on TikTok for her viral dance videos and has since expanded into television, brand partnerships, and other entertainment ventures.

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_69ee5bbf0d208190801ee95d4f07fb16 completed April 26, 2026, 6:38 p.m.
NER Named-entity recognition batch_69f606f905688190a7c4487dc63ff305 completed May 2, 2026, 2:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11856059bc81909dd1eef6799631f3 completed May 23, 2026, 10:45 a.m.
NEDg Description generation batch_6a11865aaac881909aa388f473a6e5a3 completed May 23, 2026, 10:50 a.m.
NED2 Entity disambiguation (via description) batch_6a11873fe9708190a0ad2b27028b120a completed May 23, 2026, 10:53 a.m.
Created at: April 26, 2026, 7:36 p.m.