Triple

T30390308
Position Surface form Disambiguated ID Type / Status
Subject Natalie Babbitt E773062 entity
Predicate illustrated P2761 FINISHED
Object The Forty-Ninth Magician
The Forty-Ninth Magician is a children's picture book written by Natalie Babbitt that blends gentle fantasy with whimsical illustrations to tell the story of an inept magician seeking his place among more powerful peers.
 E1914010 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: The Forty-Ninth Magician | Statement: [Natalie Babbitt, illustrated, The Forty-Ninth Magician]
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: The Forty-Ninth Magician
Triple: [Natalie Babbitt, illustrated, The Forty-Ninth Magician]
Generated description
The Forty-Ninth Magician is a children's picture book written by Natalie Babbitt that blends gentle fantasy with whimsical illustrations to tell the story of an inept magician seeking his place among more powerful peers.

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_69f2248ef0a48190aa54d4d8ac3e5758 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6859bbd7c81909084682a99f2b9be completed May 2, 2026, 11:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27894ffa788190a5aeaa78c5d766a6 completed June 9, 2026, 3:32 a.m.
NEDg Description generation batch_6a2792b7598881909e2f59770f1fa4ef completed June 9, 2026, 4:12 a.m.
NED2 Entity disambiguation (via description) batch_6a27932c8724819091d2796739454e38 completed June 9, 2026, 4:14 a.m.
Created at: April 29, 2026, 8:02 p.m.