Triple

T12134954
Position Surface form Disambiguated ID Type / Status
Subject Zamboanga del Norte E289032 entity
Predicate hasCity P316 FINISHED
Object Dapitan E251471 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: Dapitan | Statement: [Zamboanga del Norte, hasCity, Dapitan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dapitan
Context triple: [Zamboanga del Norte, hasCity, Dapitan]
  • A. Dapitan chosen
    Dapitan is a historic coastal city in the Zamboanga Peninsula of the Philippines, best known as the place of exile of national hero José Rizal.
  • B. Dinalungan
    Dinalungan is a coastal municipality in the province of Aurora in the Philippines, known for its rural landscapes and Pacific shoreline.
  • C. Tadyawan
    Tadyawan is an Austronesian language spoken by the Mangyan people on the island of Mindoro in the Philippines.
  • D. Pantabangan
    Pantabangan is a municipality in the Philippine province of Nueva Ecija known for the Pantabangan Dam and its role in irrigation and hydroelectric power generation.
  • E. Kabuntalan
    Kabuntalan is a municipality in the province of Maguindanao del Norte in the Philippines, known for its location along the Rio Grande de Mindanao and its predominantly Maguindanaon population.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9158c59e0819094d4522a107482b2 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64b83c15081908d2ed4c6d2e7534b completed May 2, 2026, 7:07 p.m.
Created at: April 8, 2026, 9:49 p.m.