Triple

T7603475
Position Surface form Disambiguated ID Type / Status
Subject Tabora–Mpanda railway E180041 entity
Predicate terminusB P388 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: [Tabora–Mpanda railway, terminusB, Mpanda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mpanda
Context triple: [Tabora–Mpanda railway, terminusB, 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_69c69f3567008190ab01d2ca7b53584a completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9fa633081909660f653f5b073cd completed March 27, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89a9dd42c8190bd03e960ebad8df9 completed March 29, 2026, 3:21 a.m.
Created at: March 27, 2026, 3:54 p.m.