Triple

T26890651
Position Surface form Disambiguated ID Type / Status
Subject Cornelius Vander Starr E677160 entity
Predicate hasPhilanthropicOrganizationNamedAfter P167306 FINISHED
Object Starr Foundation
The Starr Foundation is a major New York-based charitable foundation that provides grants worldwide in areas such as education, healthcare, public policy, culture, and international relations.
E1747388 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: Starr Foundation | Statement: [Cornelius Vander Starr, hasPhilanthropicOrganizationNamedAfter, Starr Foundation]
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: Starr Foundation
Triple: [Cornelius Vander Starr, hasPhilanthropicOrganizationNamedAfter, Starr Foundation]
Generated description
The Starr Foundation is a major New York-based charitable foundation that provides grants worldwide in areas such as education, healthcare, public policy, culture, and international relations.

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_69eee9bc0c90819085608c8bdc513a57 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f66ac5c1e08190ac37796193cc6ffc completed May 2, 2026, 9:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121e9fe44881909c65bf5de48dd2c4 completed May 23, 2026, 9:39 p.m.
NEDg Description generation batch_6a121f5b854481908b2c1abbbdc7cc89 completed May 23, 2026, 9:42 p.m.
NED2 Entity disambiguation (via description) batch_6a121fd8924881909fe3b5e2eeb1a407 completed May 23, 2026, 9:44 p.m.
Created at: April 27, 2026, 5:44 a.m.