Triple

T13876593
Position Surface form Disambiguated ID Type / Status
Subject Karamoja region E333598 entity
Predicate contains P35 FINISHED
Object Kotido District E1009458 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: Kotido District | Statement: [Karamoja region, contains, Kotido District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kotido District
Context triple: [Karamoja region, contains, Kotido District]
  • A. Kotido District chosen
    Kotido District is an administrative district in northeastern Uganda known for its predominantly pastoralist Karamojong communities and semi-arid landscape.
  • B. Pallisa District
    Pallisa District is an administrative district in eastern Uganda known for its predominantly rural communities and agriculture-based economy.
  • C. Dokolo District
    Dokolo District is a rural administrative district in northern Uganda, traditionally inhabited by the Lango people.
  • D. Kotoni district
    Kotoni district is a residential and commercial neighborhood in Nishi-ku, Sapporo, known for its convenient transport links and local shopping streets.
  • E. Goromonzi District
    Goromonzi District is an administrative district in northeastern Zimbabwe known for its agricultural activities and proximity to the capital, Harare.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0be556708190bbcf0b3583f677e3 completed April 14, 2026, 9:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd6474da3081909be6b892ef8cc73e completed May 8, 2026, 4:20 a.m.
Created at: April 9, 2026, 10:15 p.m.