Triple

T35234974
Position Surface form Disambiguated ID Type / Status
Subject John Zaller E1017348 entity
Predicate hasAcademicConcept P531 FINISHED
Object Receive-Accept-Sample model
The Receive-Accept-Sample model is John Zaller’s influential theory of public opinion formation, explaining how individuals receive political information, decide whether to accept it, and later sample from accepted considerations when expressing opinions.
 E2131005 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: Receive-Accept-Sample model | Statement: [John Zaller, hasAcademicConcept, Receive-Accept-Sample model]
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: Receive-Accept-Sample model
Triple: [John Zaller, hasAcademicConcept, Receive-Accept-Sample model]
Generated description
The Receive-Accept-Sample model is John Zaller’s influential theory of public opinion formation, explaining how individuals receive political information, decide whether to accept it, and later sample from accepted considerations when expressing opinions.

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_69f76de12e4c8190bc46b71a32858356 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78eecd8d081908300f4523e45e32c completed May 3, 2026, 6:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38041fe36c819084cfdfe59aac93e7 completed June 21, 2026, 3:32 p.m.
NEDg Description generation batch_6a3804add67c819096139f4115a709d6 completed June 21, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a38063b3520819080ba23f3dad18048 completed June 21, 2026, 3:41 p.m.
Created at: May 3, 2026, 4:02 p.m.