Triple

T13697642
Position Surface form Disambiguated ID Type / Status
Subject Bentota E328428 entity
Predicate hasAttraction P105 FINISHED
Object Bentota Beach E1053338 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: Bentota Beach | Statement: [Bentota, hasAttraction, Bentota Beach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bentota Beach
Context triple: [Bentota, hasAttraction, Bentota Beach]
  • A. Bentota Beach chosen
    Bentota Beach is a popular coastal tourist destination in Sri Lanka known for its golden sands, water sports, and resort hotels along the Indian Ocean.
  • B. Matara Beach
    Matara Beach is a scenic coastal stretch in southern Sri Lanka known for its golden sands, palm-fringed shoreline, and relaxed seaside atmosphere.
  • C. Bentota
    Bentota is a popular coastal resort town in southwestern Sri Lanka, known for its beaches, river, and water sports tourism.
  • D. Manora Beach
    Manora Beach is a popular seaside destination near Karachi, Pakistan, known for its sandy shoreline, recreational activities, and views of the Arabian Sea.
  • E. Tangalle Beach
    Tangalle Beach is a tranquil, palm-fringed stretch of coastline in southern Sri Lanka known for its golden sands, turquoise waters, and relatively uncrowded, laid-back atmosphere.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc878b57c819094e7ea6d1a64211f completed April 12, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79453395481909d651cb3a128f23d completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:54 p.m.