Triple

T20381483
Position Surface form Disambiguated ID Type / Status
Subject Harold F. Johnson Foundation E497839 entity
Predicate namedAfter P63 FINISHED
Object Harold F. Johnson
Harold F. Johnson was a benefactor whose philanthropy and legacy in charitable giving led to the establishment of the Harold F. Johnson Foundation in his name.
E2287020 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: Harold F. Johnson | Statement: [Harold F. Johnson Foundation, namedAfter, Harold F. Johnson]
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: Harold F. Johnson
Triple: [Harold F. Johnson Foundation, namedAfter, Harold F. Johnson]
Generated description
Harold F. Johnson was a benefactor whose philanthropy and legacy in charitable giving led to the establishment of the Harold F. Johnson Foundation in his name.

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_69e0b4a5b7908190a972e4e7e698ae94 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e678b0ee708190bdbe4aab28a61525 completed April 20, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4756b7565c81908c86b6eadf00642a completed July 3, 2026, 6:29 a.m.
NEDg Description generation batch_6a4757ab61fc8190afaddd24e84be636 completed July 3, 2026, 6:33 a.m.
NED2 Entity disambiguation (via description) batch_6a47583de450819085171db142fd6c80 completed July 3, 2026, 6:35 a.m.
Created at: April 16, 2026, 11:27 a.m.