Triple

T3754262
Position Surface form Disambiguated ID Type / Status
Subject Harare–Beitbridge highway E82006 entity
Predicate passesNear P416 FINISHED
Object Masvingo E11625 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: Masvingo | Statement: [Harare–Beitbridge highway, passesNear, Masvingo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Masvingo
Context triple: [Harare–Beitbridge highway, passesNear, Masvingo]
  • A. Masvingo chosen
    Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
  • B. Harare
    Harare is the largest city and main economic, political, and cultural center of Zimbabwe.
  • C. Mutare
    Mutare is a major city in eastern Zimbabwe, serving as the capital of Manicaland Province and an important commercial and transport hub near the border with Mozambique.
  • D. Marondera
    Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
  • E. Kasane
    Kasane is a small town in northern Botswana that serves as a key gateway and service hub for visitors to Chobe National Park and the surrounding wildlife areas.
  • 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_69ad8b1db40081908b61ffa6b78afd4d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb94ffc08190a7fd1ce71a15f787 completed March 8, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5336b8d308190a1886ab637173b35 completed March 14, 2026, 10:07 a.m.
Created at: March 8, 2026, 3:35 p.m.