Triple

T33819377
Position Surface form Disambiguated ID Type / Status
Subject Miss Rabbit E866783 entity
Predicate voicedBy P2181 FINISHED
Object Sarah Ann Kennedy
Sarah Ann Kennedy is a British voice actress, writer, and director best known for voicing Miss Rabbit and Mummy Rabbit in the animated children's series "Peppa Pig."
E2069301 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: Sarah Ann Kennedy | Statement: [Miss Rabbit, voicedBy, Sarah Ann Kennedy]
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: Sarah Ann Kennedy
Triple: [Miss Rabbit, voicedBy, Sarah Ann Kennedy]
Generated description
Sarah Ann Kennedy is a British voice actress, writer, and director best known for voicing Miss Rabbit and Mummy Rabbit in the animated children's series "Peppa Pig."

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_69f349911a8c81908478662194b23d8c completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fff809b881909c0c303f693eb3bc completed May 3, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a366e9ed3cc8190b10b5c83a7641e87 completed June 20, 2026, 10:42 a.m.
NEDg Description generation batch_6a366f2eab708190a7ab0579a49a7627 completed June 20, 2026, 10:45 a.m.
NED2 Entity disambiguation (via description) batch_6a3670cf75cc81909ea1a134d965c02c completed June 20, 2026, 10:51 a.m.
Created at: May 1, 2026, 1:46 a.m.