Triple

T27619793
Position Surface form Disambiguated ID Type / Status
Subject Michael Hurll Television E700544 entity
Predicate namedAfter P63 FINISHED
Object Michael Hurll
Michael Hurll was a British television producer best known for his work on popular light entertainment and comedy shows, including "Top of the Pops" and "The Two Ronnies."
E1838045 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: Michael Hurll | Statement: [Michael Hurll Television, namedAfter, Michael Hurll]
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: Michael Hurll
Triple: [Michael Hurll Television, namedAfter, Michael Hurll]
Generated description
Michael Hurll was a British television producer best known for his work on popular light entertainment and comedy shows, including "Top of the Pops" and "The Two Ronnies."

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_69ef6a4f1d9c8190b0705acda054368d completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f630dafea481909f5f59c5ed3269ee completed May 2, 2026, 5:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24d3d5594481909fdeae18386ba396 completed June 7, 2026, 2:13 a.m.
NEDg Description generation batch_6a24d8a7ef3c819084ae4a614edace9b completed June 7, 2026, 2:34 a.m.
NED2 Entity disambiguation (via description) batch_6a24d901847c8190bde79e92232f03b0 completed June 7, 2026, 2:35 a.m.
Created at: April 27, 2026, 2:14 p.m.