Triple

T21501942
Position Surface form Disambiguated ID Type / Status
Subject Quezon Province E530495 entity
Predicate hasMunicipality P847 FINISHED
Object Agdangan 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: Agdangan | Statement: [Quezon Province, hasMunicipality, Agdangan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Agdangan
Context triple: [Quezon Province, hasMunicipality, Agdangan]
  • A. Agdangan chosen
    Agdangan is a coastal municipality in the province of Quezon in the Philippines, known for its agricultural economy and rural community character.
  • B. Angadanan
    Angadanan is a landlocked agricultural municipality in the province of Isabela in the Cagayan Valley region of the Philippines.
  • C. Ampatuan
    Ampatuan is a municipality in the Philippine province of Maguindanao, known for its political clan and association with the 2009 Maguindanao massacre.
  • D. Kapangan
    Kapangan is a rural municipality in the mountainous province of Benguet in the Philippines, known for its cool climate, highland farms, and scenic Cordillera landscapes.
  • 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 (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_69e0c45bd15481909fba5910765cdda2 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea5d209881908754eb07a47e478a completed April 23, 2026, 9:46 a.m.
Created at: April 16, 2026, 6:24 p.m.