Triple

T24544882
Position Surface form Disambiguated ID Type / Status
Subject Charles E. Fuller E607193 entity
Predicate notableWork P4 FINISHED
Object Old Fashioned Revival Hour
Old Fashioned Revival Hour was a popular mid-20th-century evangelical Christian radio program known for its preaching, gospel music, and wide national and international reach.
 E1638904 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: Old Fashioned Revival Hour | Statement: [Charles E. Fuller, notableWork, Old Fashioned Revival Hour]
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: Old Fashioned Revival Hour
Triple: [Charles E. Fuller, notableWork, Old Fashioned Revival Hour]
Generated description
Old Fashioned Revival Hour was a popular mid-20th-century evangelical Christian radio program known for its preaching, gospel music, and wide national and international reach.

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_69e2c4c9bf94819082d05da6f5c29907 completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a8c84c648190bcc7edc0ac859cb0 completed April 30, 2026, 12:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0feea8d17c8190912b4efee020af73 completed May 22, 2026, 5:50 a.m.
NEDg Description generation batch_6a0fef6feb088190870b41df1edb338e completed May 22, 2026, 5:53 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff08d9fac81909ea8af6e6b10102a completed May 22, 2026, 5:58 a.m.
Created at: April 18, 2026, 2:26 a.m.