Triple

T18074146
Position Surface form Disambiguated ID Type / Status
Subject Kingdom of Bunyoro E432509 entity
Predicate formerCapital P3417 FINISHED
Object Masindi NE NERFINISHED

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: Masindi | Statement: [Kingdom of Bunyoro, formerCapital, Masindi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Masindi
Context triple: [Kingdom of Bunyoro, formerCapital, Masindi]
  • A. Masindi chosen
    Masindi is a town in western Uganda that serves as a key gateway and service center for visitors to Murchison Falls National Park.
  • B. Manzini
    Manzini is a major city in Eswatini that serves as an important commercial and transport hub of the country.
  • C. Mogoro
    Mogoro is a small town and municipality in central-western Sardinia, Italy, known for its traditional crafts and wine production.
  • D. Mbeya
    Mbeya is a major city in southwestern Tanzania, serving as a commercial and transport hub near the Zambian border.
  • E. Mzimba
    Mzimba is a town in northern Malawi that serves as the administrative center of Mzimba District, known for its agricultural activities and Ngoni cultural heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9070cac81909fa9473fb1c3f1c7 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ccefcdc4819086d0b224731bfc4d completed April 19, 2026, 12:39 p.m.
Created at: April 10, 2026, 10:26 a.m.