Triple

T20581767
Position Surface form Disambiguated ID Type / Status
Subject Hemmingson Center E505673 entity
Predicate namedAfter P63 FINISHED
Object John J. Hemmingson
John J. Hemmingson is a philanthropist and major benefactor associated with Gonzaga University, for whom the university’s Hemmingson Center is named.
 E1687268 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: John J. Hemmingson | Statement: [Hemmingson Center, namedAfter, John J. Hemmingson]
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: John J. Hemmingson
Triple: [Hemmingson Center, namedAfter, John J. Hemmingson]
Generated description
John J. Hemmingson is a philanthropist and major benefactor associated with Gonzaga University, for whom the university’s Hemmingson Center is named.

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_69e0b4b9669c8190b8e81fc72817d42c completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a90f7e34819086b1745dcd53ba25 completed April 20, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10b6f49d588190960982c7aead9b7b completed May 22, 2026, 8:05 p.m.
NEDg Description generation batch_6a10b84949448190ba06c85d0f19215b completed May 22, 2026, 8:10 p.m.
NED2 Entity disambiguation (via description) batch_6a10b9606818819094491a74c5922378 completed May 22, 2026, 8:15 p.m.
Created at: April 16, 2026, 11:40 a.m.