Triple

T5322137
Position Surface form Disambiguated ID Type / Status
Subject loanDepot E121697 entity
Predicate hasEmployee P2308 FINISHED
Object Anthony Hsieh E512242 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: Anthony Hsieh | Statement: [loanDepot, hasEmployee, Anthony Hsieh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anthony Hsieh
Context triple: [loanDepot, hasEmployee, Anthony Hsieh]
  • A. Anthony Hsieh chosen
    Anthony Hsieh is an American entrepreneur best known as the founder and former CEO of loanDepot, one of the largest nonbank mortgage lenders in the United States.
  • B. Tony Hsieh
    Tony Hsieh was an American entrepreneur and venture capitalist best known for transforming Zappos into a pioneering online retailer celebrated for its customer service–driven culture.
  • C. Reid Hoffman
    Reid Hoffman is an American entrepreneur, venture capitalist, and co-founder of LinkedIn, known for his influential role in the tech industry and philanthropy.
  • D. John Donahoe
    John Donahoe is an American business executive best known as the CEO of Nike, Inc. and former CEO of eBay and ServiceNow.
  • E. Alex Karp
    Alex Karp is an American billionaire entrepreneur and co-founder CEO of Palantir Technologies, known for its data analytics software used by governments and large institutions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69bd463d956c819088105c3db802c017 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd8577ba3881909a28cbf744648256 completed March 20, 2026, 5:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf290bb4148190b6f98fcd36d03c02 completed March 21, 2026, 11:26 p.m.
Created at: March 20, 2026, 1:59 p.m.