Triple

T22398549
Position Surface form Disambiguated ID Type / Status
Subject Maharagama Divisional Secretariat E553698 entity
Predicate administrativeCenter P1474 FINISHED
Object Maharagama 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: Maharagama | Statement: [Maharagama Divisional Secretariat, administrativeCenter, Maharagama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maharagama
Context triple: [Maharagama Divisional Secretariat, administrativeCenter, Maharagama]
  • A. Maharagama chosen
    Maharagama is a suburban city in the Colombo District of Sri Lanka, known as a densely populated residential and commercial hub within the Colombo metropolitan area.
  • B. Peradeniya
    Peradeniya is a town in central Sri Lanka renowned for its historic university and expansive Royal Botanical Gardens.
  • C. Dematagoda
    Dematagoda is a residential and commercial suburb within the city of Colombo, Sri Lanka.
  • D. Nugegoda
    Nugegoda is a busy suburban town and commercial hub in the Colombo District of Sri Lanka, known for its dense population, shopping areas, and proximity to the administrative capital.
  • E. Badulla
    Badulla is a major town in Sri Lanka’s central highlands, known as the capital of Uva Province and a regional hub surrounded by tea plantations and scenic mountain landscapes.
  • 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_69e11e4da7048190b4387d422a9a0de5 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15861ac248190a967f534feea0265 completed April 29, 2026, 1:01 a.m.
Created at: April 16, 2026, 8:46 p.m.