Triple

T12981987
Position Surface form Disambiguated ID Type / Status
Subject Matara District E321672 entity
Predicate hasCoastalTown P969 FINISHED
Object Dikwella E1013906 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: Dikwella | Statement: [Matara District, hasCoastalTown, Dikwella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dikwella
Context triple: [Matara District, hasCoastalTown, Dikwella]
  • A. Dikwella chosen
    Dikwella is a coastal town in southern Sri Lanka known for its beaches and the towering Wewurukannala Vihara Buddha statue.
  • B. Dikwa
    Dikwa is a historic town in northeastern Nigeria that once served as a key political and administrative center of the Borno Empire.
  • C. Biloela
    Biloela is a rural town in Queensland, Australia, known as an agricultural and administrative centre for the surrounding Central Queensland region.
  • D. Maleka
    Maleka is a feminine given name, typically considered a variant spelling of Malika and used in various cultures.
  • E. Titwala
    Titwala is a suburban town in the Thane district of Maharashtra, India, known for its Siddhivinayak Mahaganapati Temple and connectivity to Mumbai via the suburban railway network.
  • 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_69d8076479b8819090afce3591939cdf completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e5ca33481909a6cb06c636889f9 completed April 10, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0f95c548190a6fc2c1ea98246c3 completed May 3, 2026, 3:28 a.m.
Created at: April 9, 2026, 8:39 p.m.