Triple

T4719439
Position Surface form Disambiguated ID Type / Status
Subject Pangasinan language E104727 entity
Predicate hasDialects P4251 FINISHED
Object Central Pangasinan E104727 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: Central Pangasinan | Statement: [Pangasinan language, hasDialects, Central Pangasinan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Central Pangasinan
Context triple: [Pangasinan language, hasDialects, Central Pangasinan]
  • A. Norte Samareño
    Norte Samareño is the term used to refer to residents or natives of the Philippine province of Northern Samar.
  • B. Pampanga
    Pampanga is a province in the Central Luzon region of the Philippines, known for its rich culinary heritage, vibrant festivals, and significant role in the country’s history and culture.
  • C. Bikol Central
    Bikol Central is a major Austronesian language spoken in the Bicol Region of the Philippines, particularly in and around the city of Naga in Camarines Sur.
  • 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. Pangasinan chosen
    Pangasinan is an Austronesian language spoken primarily in the Pangasinan province and surrounding areas of northwestern Luzon in the Philippines.
  • 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_69bd43ec4a348190bc41afae43375e71 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6428e9e081908ce4041183cad13b completed March 20, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69be108bc0048190aeea8674f75105e5 completed March 21, 2026, 3:29 a.m.
Created at: March 20, 2026, 1:18 p.m.