Triple

T24763382
Position Surface form Disambiguated ID Type / Status
Subject The Pothunters E619512 entity
Predicate hasIllustrationsBy P2761 FINISHED
Object R. Noel Pocock
R. Noel Pocock was an illustrator known for providing artwork for early 20th-century books, including school stories such as P. G. Wodehouse’s "The Pothunters."
E1662333 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: R. Noel Pocock | Statement: [The Pothunters, hasIllustrationsBy, R. Noel Pocock]
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: R. Noel Pocock
Triple: [The Pothunters, hasIllustrationsBy, R. Noel Pocock]
Generated description
R. Noel Pocock was an illustrator known for providing artwork for early 20th-century books, including school stories such as P. G. Wodehouse’s "The Pothunters."

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_69e2fabbea94819092ed41348909622f completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f410a330f0819081bc60b9275d883d completed May 1, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a104882d9e88190afc2212fb54d0b73 completed May 22, 2026, 12:13 p.m.
NEDg Description generation batch_6a10496ad0748190b797fea89fc9472d completed May 22, 2026, 12:17 p.m.
NED2 Entity disambiguation (via description) batch_6a104bc667e48190bb0feadc5b324cde completed May 22, 2026, 12:27 p.m.
Created at: April 18, 2026, 4:28 a.m.