Triple

T14596802
Position Surface form Disambiguated ID Type / Status
Subject Biliran Province E342589 entity
Predicate hasMunicipality P847 FINISHED
Object Cabucgayan E343543 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: Cabucgayan | Statement: [Biliran Province, hasMunicipality, Cabucgayan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cabucgayan
Context triple: [Biliran Province, hasMunicipality, Cabucgayan]
  • A. Cabucgayan chosen
    Cabucgayan is a coastal municipality in the province of Biliran in the Eastern Visayas region of the Philippines.
  • B. Cabugao
    Cabugao is a coastal municipality in the province of Ilocos Sur in the Philippines, known for its beaches and agricultural economy.
  • C. Cagbang
    Cagbang is a barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
  • D. Cantilan
    Cantilan is a coastal municipality in the province of Surigao del Sur in the Philippines, known for its beaches, marine resources, and agricultural activities.
  • E. Kapangan
    Kapangan is a rural municipality in the mountainous province of Benguet in the Philippines, known for its cool climate, highland farms, and scenic Cordillera landscapes.
  • 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_69d822ddc0f081909cd8163c7de298cd completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb43581348190b5362251c3a89654 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde169eb6481909d7fac6d984a2af1 completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:25 a.m.