Triple

T2264620
Position Surface form Disambiguated ID Type / Status
Subject Manila Bay E50116 entity
Predicate borders P224 FINISHED
Object Pampanga Province 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 Province | Statement: [Manila Bay, borders, Pampanga Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pampanga Province
Context triple: [Manila Bay, borders, Pampanga Province]
  • 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 an Austronesian language spoken primarily in the Pangasinan province and surrounding areas of northwestern Luzon in the Philippines.
  • C. 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.
  • 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. Batangas
    Batangas is a province in the Calabarzon region of the Philippines known for its beaches, diving spots, and the Taal Volcano.
  • 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_69a88b01e0048190ba96431b5f990ba9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc18ed0708190aa3156e9d35120c3 completed March 7, 2026, 6:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea86527d08190a1332d133fbd7293 completed March 9, 2026, 11 a.m.
Created at: March 4, 2026, 7:48 p.m.