Triple

T29284588
Position Surface form Disambiguated ID Type / Status
Subject Allegra Kent E742472 entity
Predicate notableWork P4 FINISHED
Object Allegra Kent’s The Dancer’s Body Book
Allegra Kent’s *The Dancer’s Body Book* is a guide that blends memoir and practical advice on dance technique, body care, and wellness from the famed New York City Ballet ballerina.
E1859199 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: Allegra Kent’s The Dancer’s Body Book | Statement: [Allegra Kent, notableWork, Allegra Kent’s The Dancer’s Body Book]
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: Allegra Kent’s The Dancer’s Body Book
Triple: [Allegra Kent, notableWork, Allegra Kent’s The Dancer’s Body Book]
Generated description
Allegra Kent’s *The Dancer’s Body Book* is a guide that blends memoir and practical advice on dance technique, body care, and wellness from the famed New York City Ballet ballerina.

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_69f09121ed8c8190b4cb27be3619c262 completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f665191d888190b4ab2c4bbd7725cb completed May 2, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a258941567881909ef3305fa7060195 completed June 7, 2026, 3:07 p.m.
NEDg Description generation batch_6a258dc9da8c819093b3085ae2f81b0f completed June 7, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_6a2591b07f9c8190b96d783d20353801 completed June 7, 2026, 3:43 p.m.
Created at: April 28, 2026, 12:57 p.m.