Triple

T3754836
Position Surface form Disambiguated ID Type / Status
Subject Kulitan script E82020 entity
Predicate region P40 FINISHED
Object Pampanga E83192 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: Pampanga | Statement: [Kulitan script, region, Pampanga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pampanga
Context triple: [Kulitan script, region, Pampanga]
  • A. Pampanga chosen
    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.
  • B. 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.
  • C. Pangasinan
    Pangasinan is an Austronesian language spoken primarily in the Pangasinan province and surrounding areas of northwestern Luzon in the Philippines.
  • D. Nueva Ecija
    Nueva Ecija is a landlocked agricultural province in Central Luzon, Philippines, known as a major rice-producing area and home to diverse ethnolinguistic groups.
  • E. Bulacan
    Bulacan is a province in the Central Luzon region of the Philippines known for its historical significance, cultural heritage, and proximity to Metro Manila.
  • 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_69ad8b1db40081908b61ffa6b78afd4d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb94ffc08190a7fd1ce71a15f787 completed March 8, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69b6131d07048190bbc735cf88d5ee60 completed March 15, 2026, 2:02 a.m.
Created at: March 8, 2026, 3:35 p.m.