Triple

T34685584
Position Surface form Disambiguated ID Type / Status
Subject Honey Bunches of Oats E890736 entity
Predicate creator P184 FINISHED
Object Vernon J. Herzing
Vernon J. Herzing is an American food industry professional best known for developing the popular breakfast cereal Honey Bunches of Oats while working at Post.
 E2293850 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: Vernon J. Herzing | Statement: [Honey Bunches of Oats, creator, Vernon J. Herzing]
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: Vernon J. Herzing
Triple: [Honey Bunches of Oats, creator, Vernon J. Herzing]
Generated description
Vernon J. Herzing is an American food industry professional best known for developing the popular breakfast cereal Honey Bunches of Oats while working at Post.

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_69f349dabc008190a18999c26682ed47 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7234cdb9c8190a6a46242de1b3926 completed May 3, 2026, 10:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7b1b8abb908190a5057c36ed92dd9c completed Aug. 11, 2026, 12:54 p.m.
NEDg Description generation batch_6a7b1bd2d2f8819085d6e530ce6bffbf completed Aug. 11, 2026, 12:55 p.m.
NED2 Entity disambiguation (via description) batch_6a7b1c211a188190b23a77a4b733a0c7 completed Aug. 11, 2026, 12:57 p.m.
Created at: May 1, 2026, 2:05 a.m.