Triple

T12981986
Position Surface form Disambiguated ID Type / Status
Subject Matara District E321672 entity
Predicate hasCoastalTown P969 FINISHED
Object Mirissa E321675 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: Mirissa | Statement: [Matara District, hasCoastalTown, Mirissa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mirissa
Context triple: [Matara District, hasCoastalTown, Mirissa]
  • A. Mirissa chosen
    Mirissa is a small coastal town in southern Sri Lanka known for its scenic beaches, surfing, and whale-watching opportunities.
  • B. Maiana
    Maiana is a low-lying coral atoll in the central Pacific nation of Kiribati, known for its traditional village life and vulnerability to sea-level rise.
  • C. Laka
    Laka is a dialect of the Sara language spoken in parts of Central Africa, particularly in Chad and neighboring regions.
  • D. Vai Malandra
    "Vai Malandra" is a hit Brazilian funk-pop song by singer Anitta that became a major cultural phenomenon and chart success in Brazil and internationally.
  • E. Mazunte
    Mazunte is a small, laid-back beach town on Mexico’s Oaxacan coast, known for its sea turtle conservation center, eco-tourism, and scenic Pacific shoreline.
  • 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.