Triple

T17849477
Position Surface form Disambiguated ID Type / Status
Subject Sorsogon City E445757 entity
Predicate isNear P350 FINISHED
Object Matnog NE NERFINISHED

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: Matnog | Statement: [Sorsogon City, isNear, Matnog]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matnog
Context triple: [Sorsogon City, isNear, Matnog]
  • A. Matnog chosen
    Matnog is a coastal municipality in the province of Sorsogon in the Philippines, known as a major ferry gateway between Luzon and the Visayas.
  • B. Manglicmot
    Manglicmot is a rural barangay (village-level administrative division) located in the municipality of San Felipe in the province of Zambales, Philippines.
  • C. Martung
    Martung is a town and administrative settlement located within Shangla District in Pakistan's Khyber Pakhtunkhwa province.
  • D. Maaninka
    Maaninka is a former rural municipality in eastern Finland, known for its lakes and agricultural landscape, that is now part of the city of Kuopio in the Northern Savonia region.
  • E. Mosnang
    Mosnang is a Swiss municipality in the canton of St. Gallen, known for its rural character and location in the Toggenburg region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f26f18819089c9e43250bee6ae completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48ffd7e2c81909a42cc7ab64e7db9 completed April 19, 2026, 8:19 a.m.
Created at: April 10, 2026, 10:16 a.m.