Triple

T2640433
Position Surface form Disambiguated ID Type / Status
Subject Matabeleland E62851 entity
Predicate majorTown P316 FINISHED
Object Gwanda E149377 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: Gwanda | Statement: [Matabeleland, majorTown, Gwanda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gwanda
Context triple: [Matabeleland, majorTown, Gwanda]
  • A. Gwanda chosen
    Gwanda is a small Zimbabwean town that serves as an administrative and commercial hub in the country’s arid south, known historically for cattle ranching and gold mining.
  • B. Kalangala
    Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
  • C. Runyankole
    Runyankole is a Bantu language spoken primarily by the Banyankole people in southwestern Uganda.
  • D. Matadi
    Matadi is a major port city in western Democratic Republic of the Congo, serving as the country’s principal seaport and a key gateway for trade between the Atlantic Ocean and the interior via the Congo River.
  • 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_69ab4c3f2dcc819082df80f5e032f690 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abd8fc8ee881908a9f6820d8934a62 completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69af90b8469881909e2c1bd1f4798464 completed March 10, 2026, 3:32 a.m.
Created at: March 6, 2026, 9:53 p.m.