Triple

T10397931
Position Surface form Disambiguated ID Type / Status
Subject Misamis Oriental E245068 entity
Predicate hasMunicipality P847 FINISHED
Object Tagoloan E819586 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: Tagoloan | Statement: [Misamis Oriental, hasMunicipality, Tagoloan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tagoloan
Context triple: [Misamis Oriental, hasMunicipality, Tagoloan]
  • A. Tagoloan chosen
    Tagoloan is a coastal municipality in Misamis Oriental, Philippines, known for its strategic location near Cagayan de Oro and its growing industrial and port activities.
  • B. Balamban
    Balamban is a coastal municipality in the province of Cebu in the Philippines, known for its shipbuilding industry and growing economic zone.
  • C. Sarangani
    Sarangani is a coastal province in the southern Philippines known for its rich marine biodiversity, tuna industry, and diverse indigenous cultures.
  • D. Karagawan
    Karagawan is a regional dialect of the Isnag language spoken by the Isnag people of northern Luzon in the Philippines.
  • E. Tanauan
    Tanauan is a city in the Calabarzon region of the Philippines known for its growing industrial zones 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9d0de448190b0bfd4d6c87d47fa completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d89f6fbc848190806d50bfad654b27 completed April 10, 2026, 6:57 a.m.
Created at: April 6, 2026, 12:07 p.m.