Triple

T13669193
Position Surface form Disambiguated ID Type / Status
Subject Maradana railway station E327703 entity
Predicate locatedInNeighbourhood P40 FINISHED
Object Maradana E556806 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: Maradana | Statement: [Maradana railway station, locatedInNeighbourhood, Maradana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maradana
Context triple: [Maradana railway station, locatedInNeighbourhood, 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. 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.
  • C. Nagamangala
    Nagamangala is a town in the Indian state of Karnataka known for its temples and role as a local commercial and administrative center.
  • D. Ruhuna
    Ruhuna is an ancient historical region in southern Sri Lanka, known for its early Sinhalese kingdoms and rich archaeological heritage.
  • E. Ruwanwella
    Ruwanwella is a small town in Sri Lanka known for its historical fort and scenic surroundings, located within the Sabaragamuwa Province.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc65832688190aea688fee0a7cbdb completed April 12, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78b0f56048190bcbc6581a8cdc0f5 completed May 3, 2026, 5:51 p.m.
Created at: April 9, 2026, 9:53 p.m.