Triple

T956516
Position Surface form Disambiguated ID Type / Status
Subject Reed Hastings E20636 entity
Predicate workedIn P1527 FINISHED
Object Swaziland E16080 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: Swaziland | Statement: [Reed Hastings, workedIn, Swaziland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swaziland
Context triple: [Reed Hastings, workedIn, Swaziland]
  • A. Eswatini chosen
    Eswatini is a small landlocked monarchy in Southern Africa known for its blend of traditional Swazi culture and modern institutions.
  • B. Lesotho
    Lesotho is a small, landlocked constitutional monarchy in Southern Africa, entirely surrounded by South Africa and known for its mountainous terrain and high-altitude settlements.
  • C. Botswana
    Botswana is a landlocked country in Southern Africa known for its stable democracy, significant diamond resources, and vast wildlife-rich landscapes including the Okavango Delta.
  • D. Zimbabwe
    Zimbabwe is a landlocked country in southern Africa known for its dramatic landscapes, diverse wildlife, and historical sites such as Victoria Falls and the Great Zimbabwe ruins.
  • E. Kwaluseni
    Kwaluseni is a town in Eswatini known primarily as the main campus site of the University of Eswatini.
  • 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_69a493b21f2881908132dcf45dcd2f36 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3f981bc819098125554eeeb6375 completed March 1, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae3032c1588190bae02f0e2152c6f1 completed March 9, 2026, 2:28 a.m.
Created at: March 1, 2026, 7:40 p.m.