Triple

T4264936
Position Surface form Disambiguated ID Type / Status
Subject Chocolate Hills E96802 entity
Predicate locatedIn P40 FINISHED
Object Bohol Province E109173 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: Bohol Province | Statement: [Chocolate Hills, locatedIn, Bohol Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bohol Province
Context triple: [Chocolate Hills, locatedIn, Bohol Province]
  • A. Romblon
    Romblon is an island province in the Philippines known for its marble industry, clear waters, and scenic beaches.
  • B. 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.
  • C. Samar Province
    Samar Province is a largely rural island province in the Eastern Visayas region of the Philippines, known for its rugged landscapes, caves, and strong Waray-speaking cultural heritage.
  • D. 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.
  • E. Bohol Island chosen
    Bohol Island is a popular island province in the central Philippines known for its Chocolate Hills, tarsier sanctuaries, and white-sand beaches.
  • 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_69b34543f06c8190915ebb1a4574ffa9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34fcad0a881908e1cac0a6da5a321 completed March 12, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5f5b3f5b88190bda71f9f053e67d7 completed March 14, 2026, 11:56 p.m.
Created at: March 12, 2026, 11:06 p.m.