Triple

T22098951
Position Surface form Disambiguated ID Type / Status
Subject Port of Cagayan de Oro E546115 entity
Predicate connectsTo P845 FINISHED
Object Bohol NE NERFINISHED

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: Bohol | Statement: [Port of Cagayan de Oro, connectsTo, Bohol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bohol
Context triple: [Port of Cagayan de Oro, connectsTo, Bohol]
  • A. Bohol Province chosen
    Bohol Province is a popular island province in the central Philippines known for its Chocolate Hills, tarsier sanctuaries, white-sand beaches, and rich cultural heritage.
  • B. Bohol Island
    Bohol Island is a popular island province in the central Philippines known for its Chocolate Hills, tarsier sanctuaries, and white-sand beaches.
  • C. Leyte
    Leyte is a large island province in the Eastern Visayas region of the Philippines, known for its rich cultural traditions and historical significance, including major World War II events.
  • D. Romblon
    Romblon is an island province in the Philippines known for its marble industry, clear waters, and scenic beaches.
  • E. Guimaras
    Guimaras is a small island province in the Philippines known for its mango production, coastal scenery, and predominantly Hiligaynon-speaking population.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e36d03c8190a83a1ba802b7231b completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129131b4c8190b443bc820d9b5c61 completed April 28, 2026, 9:39 p.m.
Created at: April 16, 2026, 8:30 p.m.