Triple

T30798461
Position Surface form Disambiguated ID Type / Status
Subject The English Game E784296 entity
Predicate executiveProducer P7225 FINISHED
Object Ben Vanstone
Ben Vanstone is a British television writer and producer known for his work on period dramas such as *The English Game* and *All Creatures Great and Small*.
 E1933035 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: Ben Vanstone | Statement: [The English Game, executiveProducer, Ben Vanstone]
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: Ben Vanstone
Triple: [The English Game, executiveProducer, Ben Vanstone]
Generated description
Ben Vanstone is a British television writer and producer known for his work on period dramas such as *The English Game* and *All Creatures Great and Small*.

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_69f224b2e2a48190b19aa43db9da5b67 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f690380ad8819093157b52b303beca completed May 3, 2026, midnight
NED1 Entity disambiguation (via context triple) batch_6a28bbd9b2a08190ab28d1fa497cfc9b completed June 10, 2026, 1:20 a.m.
NEDg Description generation batch_6a28bc947d108190801b827472733dfa completed June 10, 2026, 1:23 a.m.
NED2 Entity disambiguation (via description) batch_6a28bd11752881909989925c16498f98 completed June 10, 2026, 1:25 a.m.
Created at: April 29, 2026, 8:42 p.m.