Triple

T14048465
Position Surface form Disambiguated ID Type / Status
Subject Region V E338021 entity
Predicate hasProvince P285 FINISHED
Object Masbate E267334 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: Masbate | Statement: [Region V, hasProvince, Masbate]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Masbate
Context triple: [Region V, hasProvince, Masbate]
  • A. Masbate chosen
    Masbate is an island province in the central Philippines, known for its cattle ranches, rodeo festivals, and location between Luzon and the Visayas.
  • B. Masbateño
    Masbateño is a Central Philippine Bisayan language spoken primarily on Masbate Island in the Philippines.
  • C. Malabago
    Malabago is a barangay (village-level administrative division) within the municipality of Badian in the province of Cebu, Philippines.
  • D. Chamorga
    Chamorga is a small, remote village on the northeastern tip of Tenerife in the Canary Islands, known for its traditional rural character and scenic hiking routes through the surrounding mountains and coastline.
  • E. Marawila
    Marawila is a coastal town in Sri Lanka known for its beaches, fishing community, and tourism-oriented resorts.
  • 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_69d81c664e48819088cbd8f433aeffe5 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de3c88b5e48190b0f0149102c08992 completed April 14, 2026, 1:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbc34332448190b044f55f0f85d5e2 completed May 6, 2026, 10:40 p.m.
Created at: April 9, 2026, 10:20 p.m.