Triple

T31076282
Position Surface form Disambiguated ID Type / Status
Subject Trustee from the Toolroom E791970 entity
Predicate mainCharacter P1183 FINISHED
Object Keith Stewart
Keith Stewart is the unassuming, mechanically gifted model engineer who becomes an unlikely hero in Nevil Shute’s novel "Trustee from the Toolroom."
E1945653 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: Keith Stewart | Statement: [Trustee from the Toolroom, mainCharacter, Keith Stewart]
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: Keith Stewart
Triple: [Trustee from the Toolroom, mainCharacter, Keith Stewart]
Generated description
Keith Stewart is the unassuming, mechanically gifted model engineer who becomes an unlikely hero in Nevil Shute’s novel "Trustee from the Toolroom."

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_69f224ccdbbc81909b0cdb4cc2d70c7a completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f695bac0788190b3140755766a658e completed May 3, 2026, 12:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a292b23e16c819083a3d342fea5a473 completed June 10, 2026, 9:15 a.m.
NEDg Description generation batch_6a292cdd5ee88190926628802531846f completed June 10, 2026, 9:22 a.m.
NED2 Entity disambiguation (via description) batch_6a2930b369f4819082c70a68175249b8 completed June 10, 2026, 9:38 a.m.
Created at: April 29, 2026, 9:02 p.m.