Triple

T36160148
Position Surface form Disambiguated ID Type / Status
Subject Lifetime Achievement Award from Cooper Hewitt, Smithsonian Design Museum E1045852 entity
Predicate notableRecipient P108 FINISHED
Object Ralph Caplan
Ralph Caplan is an influential American design writer, critic, and educator known for his insightful contributions to design theory and communication.
E2171917 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: Ralph Caplan | Statement: [Lifetime Achievement Award from Cooper Hewitt, Smithsonian Design Museum, notableRecipient, Ralph Caplan]
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: Ralph Caplan
Triple: [Lifetime Achievement Award from Cooper Hewitt, Smithsonian Design Museum, notableRecipient, Ralph Caplan]
Generated description
Ralph Caplan is an influential American design writer, critic, and educator known for his insightful contributions to design theory and communication.

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_69f76e38903c8190a52887620f90aabe completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b4ca29c88190b465af89c4c88d4b completed May 3, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a390d5217e48190b91c3320e3c1aa58 completed June 22, 2026, 10:24 a.m.
NEDg Description generation batch_6a390e3d07e48190b3869fa5138dd840 completed June 22, 2026, 10:28 a.m.
NED2 Entity disambiguation (via description) batch_6a390f4f8d848190b72143928c888b70 completed June 22, 2026, 10:32 a.m.
Created at: May 3, 2026, 4:08 p.m.