Triple

T10685428
Position Surface form Disambiguated ID Type / Status
Subject Balinsasayao Twin Lakes Natural Park E251865 entity
Predicate hasAccessRoadFrom P22549 FINISHED
Object Sibulan E253492 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: Sibulan | Statement: [Balinsasayao Twin Lakes Natural Park, hasAccessRoadFrom, Sibulan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sibulan
Context triple: [Balinsasayao Twin Lakes Natural Park, hasAccessRoadFrom, Sibulan]
  • A. Sibulan chosen
    Sibulan is a coastal municipality in the Philippine province of Negros Oriental known as a gateway to Dumaguete City and for its local airport and seaport.
  • B. Guinsiliban
    Guinsiliban is a coastal municipality on the island-province of Camiguin in the Philippines, known for its rural communities and proximity to volcanic landscapes and marine attractions.
  • C. Sibunag
    Sibunag is a coastal municipality located on the island province of Guimaras in the Western Visayas region of the Philippines.
  • D. Binongko
    Binongko is an island in Indonesia’s Wakatobi archipelago, known for its traditional blacksmithing culture and remote, rugged coastal landscapes.
  • E. Sarangani
    Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd182d7c819099ff6ffb3a7083f5 completed April 9, 2026, 1:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d98894cea48190877a015dcb645bee completed April 10, 2026, 11:32 p.m.
Created at: April 8, 2026, 9:10 p.m.