Triple

T27867729
Position Surface form Disambiguated ID Type / Status
Subject Kaya Scodelario E704400 entity
Predicate portrayed P1668 FINISHED
Object Katarina Baker in Spinning Out
Katarina Baker in Spinning Out is the troubled yet fiercely determined competitive figure skater at the center of the Netflix drama series, struggling with mental health, family pressures, and the high-stakes world of elite skating.
E1790576 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: Katarina Baker in Spinning Out | Statement: [Kaya Scodelario, portrayed, Katarina Baker in Spinning Out]
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: Katarina Baker in Spinning Out
Triple: [Kaya Scodelario, portrayed, Katarina Baker in Spinning Out]
Generated description
Katarina Baker in Spinning Out is the troubled yet fiercely determined competitive figure skater at the center of the Netflix drama series, struggling with mental health, family pressures, and the high-stakes world of elite skating.

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_69ef840f12408190b539d00d79658abf completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f639493f8c819088bf8a9f586dfb7b completed May 2, 2026, 5:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f7493ae4819093364458855b92d3 completed May 24, 2026, 1:04 p.m.
NEDg Description generation batch_6a12f7d3b7048190ae5778d0d22bfd77 completed May 24, 2026, 1:06 p.m.
NED2 Entity disambiguation (via description) batch_6a12fb9650c08190a7ebdbf509b4176b completed May 24, 2026, 1:22 p.m.
Created at: April 27, 2026, 6:22 p.m.