Triple

T20155876
Position Surface form Disambiguated ID Type / Status
Subject Kegalle District E491563 entity
Predicate hasAttraction P105 FINISHED
Object Uthuwankanda NE NERFINISHED

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: Uthuwankanda | Statement: [Kegalle District, hasAttraction, Uthuwankanda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uthuwankanda
Context triple: [Kegalle District, hasAttraction, Uthuwankanda]
  • A. Uthuwankanda chosen
    Uthuwankanda is a prominent mountain in Sri Lanka famed for its scenic views and its association with the legendary bandit Saradiel.
  • B. Ukunda
    Ukunda is a coastal town in Kenya near Diani Beach, known as a popular tourist destination with a small airstrip serving regional flights.
  • C. Ukuwela
    Ukuwela is a town in Sri Lanka’s Central Province, known as a local hub within the Matale District.
  • D. Musanze
    Musanze is a major town in northern Rwanda that serves as the primary gateway for tourists visiting Volcanoes National Park and its mountain gorillas.
  • E. Kadawatha
    Kadawatha is a rapidly developing suburban town in Sri Lanka’s Western Province, known as a key transport hub on the outskirts of Colombo.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6265f8f0819080b29c752a574088 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e667e0a0488190a25d92aaf300be4a completed April 20, 2026, 5:52 p.m.
Created at: April 11, 2026, 11:34 p.m.