Triple

T34010405
Position Surface form Disambiguated ID Type / Status
Subject The Book of General Ignorance E872094 entity
Predicate author P4 FINISHED
Object John Mitchinson
John Mitchinson is a British writer, researcher, and publisher best known as the co-creator and long-time head of research for the BBC quiz show QI and co-author of its related books.
E2079947 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: John Mitchinson | Statement: [The Book of General Ignorance, author, John Mitchinson]
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: John Mitchinson
Triple: [The Book of General Ignorance, author, John Mitchinson]
Generated description
John Mitchinson is a British writer, researcher, and publisher best known as the co-creator and long-time head of research for the BBC quiz show QI and co-author of its related books.

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_69f349a08848819084b348d64c1879c3 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f70aef1d04819080add0f4b2eb2acf completed May 3, 2026, 8:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36a026fb808190adf3596d5820c3ee completed June 20, 2026, 2:13 p.m.
NEDg Description generation batch_6a36a79e5ce4819090f33ca14c338ab3 completed June 20, 2026, 2:45 p.m.
NED2 Entity disambiguation (via description) batch_6a36a829f824819097175975231be937 completed June 20, 2026, 2:48 p.m.
Created at: May 1, 2026, 1:51 a.m.