Triple

T11071765
Position Surface form Disambiguated ID Type / Status
Subject AirSWIFT E261761 entity
Predicate notableDestination P35273 FINISHED
Object Siquijor E238064 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: Siquijor | Statement: [AirSWIFT, notableDestination, Siquijor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siquijor
Context triple: [AirSWIFT, notableDestination, Siquijor]
  • A. Siquijor chosen
    Siquijor is a small island province in the central Philippines known for its white-sand beaches, coral reefs, and folklore surrounding mysticism and traditional healing.
  • B. Sorsogon
    Sorsogon is a province in the Bicol Region of the Philippines known for its coastal landscapes, whale shark interactions in Donsol, and rich Bikolano culture.
  • C. Occidental Mindoro
    Occidental Mindoro is a province in the Mimaropa region of the Philippines known for its agricultural economy, coastal communities, and proximity to the island of Mindoro’s rich marine and natural resources.
  • D. Zambales
    Zambales is a coastal province in the Central Luzon region of the Philippines, known for its beaches, mangoes, and ethnolinguistic diversity.
  • E. Capiz
    Capiz is a province in the Western Visayas region of the Philippines, known for its coastal landscapes, seafood, and use of the Hiligaynon language.
  • 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_69d6aa9983c08190b0ef61603b69feac completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7994bbb30819090410bd3d0fde33c completed April 9, 2026, 12:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ef81c65ba48190a8e2b9d7078cd978 completed April 27, 2026, 3:33 p.m.
Created at: April 8, 2026, 9:26 p.m.