Triple

T3354658
Position Surface form Disambiguated ID Type / Status
Subject Bikolano people E70576 entity
Predicate majorProvince P33670 FINISHED
Object Sorsogon E402408 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: Sorsogon | Statement: [Bikolano people, majorProvince, Sorsogon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sorsogon
Context triple: [Bikolano people, majorProvince, Sorsogon]
  • A. Sorsogon chosen
    Sorsogon is a province in the Bicol Region of the Philippines known for its coastal landscapes, whale shark interactions in Donsol, and rich Bikolano culture.
  • B. Surigao del Sur
    Surigao del Sur is a coastal province in the southeastern part of Mindanao in the Philippines, known for its rugged Pacific shoreline, waterfalls, and emerging ecotourism sites.
  • C. Pangasinan
    Pangasinan is an Austronesian language spoken primarily in the Pangasinan province and surrounding areas of northwestern Luzon in the Philippines.
  • D. Pangasinan
    Pangasinan is a populous coastal province in the Philippines known for its rich Ilocano and Pangasinense culture, agriculture, and tourism sites such as the Hundred Islands National Park.
  • E. Zambales
    Zambales is a coastal province in the Central Luzon region of the Philippines, known for its beaches, mangoes, and ethnolinguistic diversity.
  • 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_69ad85a4ef7c8190a29e2bbd6fa454e4 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb24036848190bac779d17dfdce3b completed March 8, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b73c409081909c583019d7ec1d4a completed March 14, 2026, 7:30 p.m.
Created at: March 8, 2026, 3:13 p.m.