Triple

T24326723
Position Surface form Disambiguated ID Type / Status
Subject Hee Haw E613121 entity
Predicate creator P184 FINISHED
Object Frank Peppiatt
Frank Peppiatt was a Canadian television producer and writer best known for co-creating and producing popular variety and comedy shows, including the long-running country-themed series "Hee Haw."
E1662636 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: Frank Peppiatt | Statement: [Hee Haw, creator, Frank Peppiatt]
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: Frank Peppiatt
Triple: [Hee Haw, creator, Frank Peppiatt]
Generated description
Frank Peppiatt was a Canadian television producer and writer best known for co-creating and producing popular variety and comedy shows, including the long-running country-themed series "Hee Haw."

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_69e2d7db6d5c819091194918157a7c1f completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292edb6f481909f0a6a7592fd7d6a completed April 29, 2026, 11:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10486b821081908f1c50da8872fc29 completed May 22, 2026, 12:13 p.m.
NEDg Description generation batch_6a104a2a89e08190aa35e97ffb57fc9a completed May 22, 2026, 12:20 p.m.
NED2 Entity disambiguation (via description) batch_6a104bbb9b6c81908fcc21c8c027b9de completed May 22, 2026, 12:27 p.m.
Created at: April 18, 2026, 1:54 a.m.