Triple

T22522136
Position Surface form Disambiguated ID Type / Status
Subject Maradana Railway Station E556806 entity
Predicate locatedIn P40 FINISHED
Object Maradana 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: Maradana | Statement: [Maradana Railway Station, locatedIn, Maradana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maradana
Context triple: [Maradana Railway Station, locatedIn, Maradana]
  • A. Maradana chosen
    Maradana is a densely populated, centrally located neighborhood in Colombo, Sri Lanka, known as a major transport and educational hub of the city.
  • B. Dutugemunu
    Dutugemunu was a legendary Sinhalese king of ancient Sri Lanka renowned for unifying much of the island and defeating the South Indian Chola ruler Elara.
  • C. Kaduwela
    Kaduwela is a rapidly developing suburban town in Sri Lanka’s Western Province, situated near Colombo and known for its growing residential and commercial significance.
  • D. Nagamangala
    Nagamangala is a town in the Indian state of Karnataka known for its temples and role as a local commercial and administrative center.
  • E. Yatawatta
    Yatawatta is a small town in Sri Lanka’s Central Province, known for its rural setting and agricultural surroundings within the Matale region.
  • 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_69e11e5657e881909f16ca58352c50da completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15e32b8a88190ac335d4298dd5ee3 completed April 29, 2026, 1:26 a.m.
Created at: April 16, 2026, 8:50 p.m.