Triple

T11921575
Position Surface form Disambiguated ID Type / Status
Subject Kayunga District E283668 entity
Predicate borders P224 FINISHED
Object Nakaseke District E751903 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: Nakaseke District | Statement: [Kayunga District, borders, Nakaseke District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nakaseke District
Context triple: [Kayunga District, borders, Nakaseke District]
  • A. Nakaseke District chosen
    Nakaseke District is an administrative district in Uganda known for its rural communities, agricultural activities, and historical significance in the country’s liberation struggle.
  • B. Marawara District
    Marawara District is an administrative district in eastern Afghanistan known for its mountainous terrain and location near the Pakistan border within Kunar Province.
  • C. Kinuta district
    Kinuta district is a residential neighborhood in Tokyo’s Setagaya ward, known for its large Kinuta Park and family-friendly atmosphere.
  • D. Ugu District
    Ugu District is a district municipality in the KwaZulu-Natal province of South Africa, encompassing several local municipalities along the country’s southeastern coast.
  • E. Yosa District
    Yosa District is a rural administrative district in northern Kyoto Prefecture, Japan, known for its coastal landscapes along the Sea of Japan and traditional fishing and farming communities.
  • 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_69d6ab2ce9c48190b5d39511b524f666 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e8e1b08481909ed291667035f330 completed April 10, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f48a61e120819089e44568ce7e99fe completed May 1, 2026, 11:11 a.m.
Created at: April 8, 2026, 9:45 p.m.