Triple

T33184415
Position Surface form Disambiguated ID Type / Status
Subject The Edgar Bergen and Charlie McCarthy Show E849425 entity
Predicate sponsor P67 FINISHED
Object Chase and Sanborn Coffee
Chase and Sanborn Coffee is a historic American coffee brand best known for its early and influential sponsorship of popular radio programs in the first half of the 20th century.
E2039177 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: Chase and Sanborn Coffee | Statement: [The Edgar Bergen and Charlie McCarthy Show, sponsor, Chase and Sanborn Coffee]
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: Chase and Sanborn Coffee
Triple: [The Edgar Bergen and Charlie McCarthy Show, sponsor, Chase and Sanborn Coffee]
Generated description
Chase and Sanborn Coffee is a historic American coffee brand best known for its early and influential sponsorship of popular radio programs in the first half of the 20th century.

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_69f3495e0f108190a6a7006f79f9c2c3 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d9a0608881909aa6db92c802c032 completed May 3, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3525cd97a48190928fbe734cde7fab completed June 19, 2026, 11:19 a.m.
NEDg Description generation batch_6a35267306d08190be7f605084fdf4c8 completed June 19, 2026, 11:22 a.m.
NED2 Entity disambiguation (via description) batch_6a3526dd7ef881908473f30391e82cfa completed June 19, 2026, 11:24 a.m.
Created at: May 1, 2026, 1:29 a.m.