Triple

T12889483
Position Surface form Disambiguated ID Type / Status
Subject Karuma Falls E308319 entity
Predicate hasLanguageOfToponym P24399 FINISHED
Object Luo E45322 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: Luo | Statement: [Karuma Falls, hasLanguageOfToponym, Luo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luo
Context triple: [Karuma Falls, hasLanguageOfToponym, Luo]
  • A. Luo chosen
    Luo is a Nilotic language spoken primarily by the Luo people of East Africa, especially in Kenya, Uganda, and Tanzania.
  • B. Luoyi
    Luoyi was an ancient Chinese city that served as a major political and cultural center of the Zhou dynasty.
  • C. Liao
    Liao is a surname of Chinese origin borne by various notable individuals across fields such as acting, politics, and academia.
  • D. Yangluo
    Yangluo is a town in Wuhan, Hubei Province, China, known as an industrial and port area along the Yangtze River.
  • E. Lingbo
    Lingbo is a small village in central Sweden located within Ockelbo Municipality in Gävleborg County.
  • 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_69d7bdf7c1f0819098102569a8d8cbf5 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9714581988190afc720ffd7797860 completed April 10, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a5598ad08190bad57ccfb4e4e2b6 completed May 3, 2026, 1:31 a.m.
Created at: April 9, 2026, 5:39 p.m.