Triple

T1639207
Position Surface form Disambiguated ID Type / Status
Subject Katavi Region E35428 entity
Predicate capital P234 FINISHED
Object Mpanda E179086 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: Mpanda | Statement: [Katavi Region, capital, Mpanda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mpanda
Context triple: [Katavi Region, capital, Mpanda]
  • A. Mpanda chosen
    Mpanda is a town in western Tanzania that serves as an important administrative and commercial hub for the surrounding region.
  • B. 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.
  • C. Tabora
    Tabora is a historic town in western Tanzania known as a regional trade center and former hub of 19th-century caravan routes.
  • D. Masvingo
    Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
  • E. 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.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90a1c2b148190b6610237d5bede10 completed March 5, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad79847cbc8190be99c66424034bce completed March 8, 2026, 1:28 p.m.
Created at: March 4, 2026, 7:28 p.m.