Triple

T10611133
Position Surface form Disambiguated ID Type / Status
Subject Negros Occidental E276009 entity
Predicate hasCity P316 FINISHED
Object Kabankalan E380065 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: Kabankalan | Statement: [Negros Occidental, hasCity, Kabankalan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kabankalan
Context triple: [Negros Occidental, hasCity, Kabankalan]
  • A. Kabankalan chosen
    Kabankalan is a major inland city in the province of Negros Occidental in the Philippines, known as a commercial and agricultural hub in the southern part of the island.
  • B. Kidapawan
    Kidapawan is a city in the Philippines that serves as the capital of Cotabato province on the island of Mindanao.
  • C. Dipaculao
    Dipaculao is a coastal municipality in the Philippine province of Aurora known for its beaches, surfing spots, and scenic mountain landscapes.
  • D. Koronadal
    Koronadal is a city in the Philippines that serves as the capital of South Cotabato and the regional administrative center of Soccsksargen.
  • E. Baliuag
    Baliuag is a first-class municipality in the province of Bulacan in the Philippines, known as a commercial and educational hub in Central Luzon.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6df5a1450819082ad445712fb7868 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69dff76eef4c8190b4fe681a9431207d completed April 15, 2026, 8:39 p.m.
Created at: April 8, 2026, 7:33 p.m.