Triple

T6561910
Position Surface form Disambiguated ID Type / Status
Subject Kongo Central Province E153802 entity
Predicate hasLargestCity P235 FINISHED
Object Matadi E161892 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: Matadi | Statement: [Kongo Central Province, hasLargestCity, Matadi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matadi
Context triple: [Kongo Central Province, hasLargestCity, Matadi]
  • A. Matadi chosen
    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.
  • B. Massinga
    Massinga is a coastal town in southern Mozambique that serves as an important local center within Inhambane Province.
  • C. Mpanda
    Mpanda is a town in western Tanzania that serves as an important administrative and commercial hub for the surrounding region.
  • D. Butembo
    Butembo is a major commercial city in eastern Democratic Republic of the Congo, known as a trading hub and economic center in North Kivu.
  • E. Marondera
    Marondera is a town in eastern Zimbabwe known as an agricultural and educational center within the Mashonaland region.
  • 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_69c6880cb35881909b763eb0125236b9 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae38e94081908f964d130f9147d8 completed March 27, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7127fc0a081909589c2a05e457866 completed March 27, 2026, 11:27 p.m.
Created at: March 27, 2026, 1:52 p.m.