Triple

T20540969
Position Surface form Disambiguated ID Type / Status
Subject Runway 09/27 E504330 entity
Predicate hasCountry P846 FINISHED
Object Zimbabwe NE NERFINISHED

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: Zimbabwe | Statement: [Runway 09/27, hasCountry, Zimbabwe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zimbabwe
Context triple: [Runway 09/27, hasCountry, Zimbabwe]
  • A. Zimbabwe chosen
    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.
  • B. Zambia and Zimbabwe
    Zambia and Zimbabwe are neighboring landlocked countries in southern Africa that share the famous Victoria Falls along their common border.
  • C. Zimbabwe and Mozambique
    Zimbabwe and Mozambique are neighboring countries in southeastern Africa that share borders, rivers, and ecosystems, including the Pungwe River basin.
  • D. Botswana and Zimbabwe
    Botswana and Zimbabwe are neighboring landlocked countries in Southern Africa that share close historical, economic, and ecological ties.
  • E. Zambia
    Zambia is a landlocked country in south-central Africa known for the Victoria Falls on the Zambezi River, diverse wildlife, and copper-rich economy.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4b476648190bc6019622ae54d3c completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a29224f081908298d104161c5bb9 completed April 20, 2026, 10:02 p.m.
Created at: April 16, 2026, 11:37 a.m.