Triple

T19825939
Position Surface form Disambiguated ID Type / Status
Subject Anda, Bohol E476325 entity
Predicate hasProvince P285 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: [Anda, Bohol, hasProvince, Bohol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bohol
Context triple: [Anda, Bohol, hasProvince, 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_69d8e51c7c188190b926f3a2a7b5f881 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e656c9e7348190a569a40bd1fca6ba completed April 20, 2026, 4:39 p.m.
Created at: April 10, 2026, 1:50 p.m.