Triple

T12015231
Position Surface form Disambiguated ID Type / Status
Subject Busoga sub-region E286006 entity
Predicate contains P35 FINISHED
Object Buyende District E954645 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: Buyende District | Statement: [Busoga sub-region, contains, Buyende District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buyende District
Context triple: [Busoga sub-region, contains, Buyende District]
  • A. Buyende District chosen
    Buyende District is an administrative district in eastern Uganda, known for its rural communities and location along the shores of Lake Kyoga.
  • B. Saha District
    Saha District is an administrative district (gu) in the southwestern part of Busan, South Korea, known for its coastal areas and residential neighborhoods.
  • C. Sawkai District
    Sawkai District is an administrative district located within Kunar Province in eastern Afghanistan, near the border with Pakistan.
  • D. Duji District
    Duji District is an administrative urban district of Huaibei City in Anhui Province, eastern China.
  • E. Mitte district
    Mitte district is a central borough of Berlin known for its historic landmarks, government buildings, and cultural institutions.
  • 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_69d6ab45a368819084fce08bf0dc3705 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903d9b17881908894be80d7c1b64e completed April 10, 2026, 2:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69f48b4535f48190ac5b2cabb4daf4af completed May 1, 2026, 11:15 a.m.
Created at: April 8, 2026, 9:47 p.m.