Triple

T3199723
Position Surface form Disambiguated ID Type / Status
Subject Rinconada Bikol E67020 entity
Predicate province P604 FINISHED
Object Camarines Sur E391245 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: Camarines Sur | Statement: [Rinconada Bikol, province, Camarines Sur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Camarines Sur
Context triple: [Rinconada Bikol, province, Camarines Sur]
  • A. Camarines Sur chosen
    Camarines Sur is a province in the Bicol Region of the Philippines known for its rich Bikolano culture, religious heritage sites, and natural attractions such as lakes, mountains, and eco-tourism destinations.
  • B. Camarines Norte
    Camarines Norte is a province in the Bicol Region of the Philippines known for its gold mining history, Pacific coastline, and islands with white-sand beaches.
  • C. Sorsogon
    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.
  • D. Batangas
    Batangas is a province in the Calabarzon region of the Philippines known for its beaches, diving spots, and the Taal Volcano.
  • E. 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.
  • 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_69ad8589bd988190afa7ed2bdffb7b33 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada9ad4b1c8190bc6ad0f025f238c8 completed March 8, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c1cbe848190a75c0e7108a5bc2c completed March 14, 2026, 11:53 a.m.
Created at: March 8, 2026, 3:07 p.m.