Triple

T34331594
Position Surface form Disambiguated ID Type / Status
Subject J. Whitney Bunting College of Business and Technology E881022 entity
Predicate namedAfter P63 FINISHED
Object J. Whitney Bunting
J. Whitney Bunting was an American academic leader and university president whose contributions to higher education, particularly in business and technology, led to a college being named in his honor.
E2090604 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: J. Whitney Bunting | Statement: [J. Whitney Bunting College of Business and Technology, namedAfter, J. Whitney Bunting]
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: J. Whitney Bunting
Triple: [J. Whitney Bunting College of Business and Technology, namedAfter, J. Whitney Bunting]
Generated description
J. Whitney Bunting was an American academic leader and university president whose contributions to higher education, particularly in business and technology, led to a college being named in his honor.

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_69f349ba96a08190b94887bae2d8ee49 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7139856d88190aba8e7cb73a69015 completed May 3, 2026, 9:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36f9d92dbc8190ad53465dff6f6573 completed June 20, 2026, 8:36 p.m.
NEDg Description generation batch_6a36fa5581dc8190ab4338ac70a8f16a completed June 20, 2026, 8:38 p.m.
NED2 Entity disambiguation (via description) batch_6a36fb292a5c81908ad8344c6ce6c4db completed June 20, 2026, 8:42 p.m.
Created at: May 1, 2026, 1:58 a.m.