Triple

T7978259
Position Surface form Disambiguated ID Type / Status
Subject Mpanda District E185500 entity
Predicate administrativeCenter P1474 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: [Mpanda District, administrativeCenter, Mpanda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mpanda
Context triple: [Mpanda District, administrativeCenter, 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. Nsanje
    Nsanje is a town in southern Malawi near the border with Mozambique, known as a key transport and trading center in the Lower Shire Valley.
  • C. Kasindi
    Kasindi is a border town in eastern Democratic Republic of the Congo, located near Uganda and serving as an important regional trade and transport hub.
  • 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. Massinga
    Massinga is a coastal town in southern Mozambique that serves as an important local center within Inhambane Province.
  • 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_69ca829851908190b4e03829353ee7c3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3bf84b1081908e60a556d984aad6 completed March 31, 2026, 3:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc938ffbb481908c4540e560469777 completed April 1, 2026, 3:40 a.m.
Created at: March 30, 2026, 5:14 p.m.