Triple

T6219619
Position Surface form Disambiguated ID Type / Status
Subject Vice President of Zimbabwe E139076 entity
Predicate locatedInTheAdministrativeTerritorialEntity P40 FINISHED
Object Harare E8616 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: Harare | Statement: [Vice President of Zimbabwe, locatedInTheAdministrativeTerritorialEntity, Harare]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harare
Context triple: [Vice President of Zimbabwe, locatedInTheAdministrativeTerritorialEntity, Harare]
  • A. Harare chosen
    Harare is the largest city and main economic, political, and cultural center of Zimbabwe.
  • B. Masvingo
    Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
  • C. Bulawayo
    Bulawayo is Zimbabwe’s second-largest city and a major industrial, cultural, and transport hub in the southwestern part of the country.
  • D. Marondera
    Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
  • E. Chinhoyi
    Chinhoyi is a town in northern Zimbabwe known as an administrative center and for the nearby Chinhoyi Caves.
  • 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062bbb768819099402d367f124639 completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e3dd76508190aba82a4a74c74bea completed March 27, 2026, 1:56 a.m.
Created at: March 22, 2026, 4:21 p.m.