Triple

T1976806
Position Surface form Disambiguated ID Type / Status
Subject Joe and Clara Tsai Foundation E42932 entity
Predicate funderOf P33009 FINISHED
Object education programs in the United States LITERAL 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: education programs in the United States | Statement: [Joe and Clara Tsai Foundation, funderOf, education programs in the United States]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: funderOf
Context triple: [Joe and Clara Tsai Foundation, funderOf, education programs in the United States]
  • A. fundedBy
    Indicates that an entity receives financial support or resources from another entity.
  • B. funderType
    Indicates the category or kind of organization or individual that provides funding in the relationship.
  • C. notFundedBy
    Indicates that one entity does not receive financial support, backing, or funding from another entity.
  • D. underlyingFoundedBy
    Indicates that an entity’s foundational creation or establishment is ultimately attributable to another entity, which serves as its underlying founder.
  • E. foundedFor
    Indicates that an entity was established or created specifically to serve, support, or benefit another entity or purpose.
  • F. None of above. chosen

Provenance (4 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_69a8871289048190b00b0d7744b7b2b1 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb3f9a87c8190816db3888787ad76 completed March 7, 2026, 5:13 a.m.
PD Predicate disambiguation batch_69abaff9a09c8190a81fa13f4b85bc79 completed March 7, 2026, 4:56 a.m.
PDg Predicate description generation batch_69abb09b27e88190bff164040fef6d7e completed March 7, 2026, 4:59 a.m.
Created at: March 4, 2026, 7:36 p.m.