Triple

T2612998
Position Surface form Disambiguated ID Type / Status
Subject Ilonggo E58819 entity
Predicate spokenIn P2266 FINISHED
Object Guimaras E56910 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: Guimaras | Statement: [Ilonggo, spokenIn, Guimaras]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guimaras
Context triple: [Ilonggo, spokenIn, Guimaras]
  • A. Guimaras chosen
    Guimaras is a small island province in the Philippines known for its mango production, coastal scenery, and predominantly Hiligaynon-speaking population.
  • B. Capiz
    Capiz is a province in the Western Visayas region of the Philippines, known for its coastal landscapes, seafood, and use of the Hiligaynon language.
  • C. Aklan
    Aklan is a province in the Philippines known for the world-famous Boracay Island and its vibrant Ati-Atihan Festival.
  • D. Samar Province
    Samar Province is a largely rural island province in the Eastern Visayas region of the Philippines, known for its rugged landscapes, caves, and strong Waray-speaking cultural heritage.
  • 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_69ab4ac444dc819099614e534dd6021f completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd87c5fec8190a428b94b90265352 completed March 7, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0310d7dd8819084d77c659b6fb0ed completed March 10, 2026, 2:56 p.m.
Created at: March 6, 2026, 9:50 p.m.