Triple

T22214564
Position Surface form Disambiguated ID Type / Status
Subject Avissawella E549040 entity
Predicate partOf P40 FINISHED
Object Colombo metropolitan region 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: Colombo metropolitan region | Statement: [Avissawella, partOf, Colombo metropolitan region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colombo metropolitan region
Context triple: [Avissawella, partOf, Colombo metropolitan region]
  • A. Colombo Metropolitan Region chosen
    The Colombo Metropolitan Region is Sri Lanka’s largest urban agglomeration and economic hub, centered on the capital city of Colombo and its surrounding suburbs.
  • B. Colombo District
    Colombo District is a key administrative region in western Sri Lanka that encompasses the nation’s commercial capital and surrounding urban and suburban areas.
  • C. Colombo
    Colombo is the largest city and commercial capital of Sri Lanka, historically significant as a key Indian Ocean trading hub.
  • D. Sri Jayawardenepura Kotte
    Sri Jayawardenepura Kotte is the administrative capital of Sri Lanka, located near Colombo and serving as the seat of the national legislature.
  • E. City of Negombo
    The City of Negombo is a major coastal urban center in western Sri Lanka, known for its fishing industry, sandy beaches, and proximity to the country’s main international airport.
  • 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_69e11e3f7e04819089806d81d5ac431e completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12b8b13f8819099ed8bebbfea3bc8 completed April 28, 2026, 9:50 p.m.
Created at: April 16, 2026, 8:37 p.m.