Triple

T13970526
Position Surface form Disambiguated ID Type / Status
Subject Rukungiri E336050 entity
Predicate near P350 FINISHED
Object Kabale E329619 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: Kabale | Statement: [Rukungiri, near, Kabale]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kabale
Context triple: [Rukungiri, near, Kabale]
  • A. Kabale chosen
    Kabale is a town in southwestern Uganda that serves as a key regional center and gateway to nearby attractions such as Bwindi Impenetrable National Park.
  • B. Kabiye
    Kabiye is a Gur language spoken primarily in northern Togo and recognized as one of the country's major national languages.
  • C. El Kabong
    El Kabong is the masked, guitar-swinging vigilante alter ego of the cartoon horse sheriff Quick Draw McGraw from classic Hanna-Barbera animations.
  • D. Kaleibar
    Kaleibar is a small historic city in northwestern Iran known for its mountainous landscapes and proximity to the Babak Castle fortress.
  • E. Manfalut
    Manfalut is a city in Upper Egypt known as an agricultural and commercial center within the Asyut region along the Nile.
  • 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_69d81c61f3508190aaf2ca0dc0002c59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e8eae40819080dd4bd25c73b6d6 completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1dc838c8190bbcfefd69ea29965 completed May 6, 2026, 8:17 p.m.
Created at: April 9, 2026, 10:18 p.m.