Triple

T33558350
Position Surface form Disambiguated ID Type / Status
Subject Wolf Hall E859546 entity
Predicate partOfSeries P1761 FINISHED
Object Thomas Cromwell trilogy
The Thomas Cromwell trilogy is Hilary Mantel’s acclaimed series of historical novels chronicling the rise and fall of Henry VIII’s chief minister Thomas Cromwell.
E859546 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: Thomas Cromwell trilogy | Statement: [Wolf Hall, partOfSeries, Thomas Cromwell trilogy]
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: Thomas Cromwell trilogy
Triple: [Wolf Hall, partOfSeries, Thomas Cromwell trilogy]
Generated description
The Thomas Cromwell trilogy is Hilary Mantel’s acclaimed series of historical novels chronicling the rise and fall of Henry VIII’s chief minister Thomas Cromwell.

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_69f3497b2b68819093207971b5e13dc8 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f710b7888190bc126708071a1ccc completed May 3, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35afd229848190833f01203fad18d8 completed June 19, 2026, 9:08 p.m.
NEDg Description generation batch_6a35b0740af88190a4a20b7f451910bd completed June 19, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_6a35b120ac408190a51a7deac3cfc57f completed June 19, 2026, 9:14 p.m.
Created at: May 1, 2026, 1:40 a.m.