Triple

T8704027
Position Surface form Disambiguated ID Type / Status
Subject Philippine Constabulary E206600 entity
Predicate secondaryAreaOfOperation P62593 FINISHED
Object urban areas of the Philippines LITERAL 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: urban areas of the Philippines | Statement: [Philippine Constabulary, secondaryAreaOfOperation, urban areas of the Philippines]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: secondaryAreaOfOperation
Context triple: [Philippine Constabulary, secondaryAreaOfOperation, urban areas of the Philippines]
  • A. secondaryTo
    Indicates that one condition, event, or factor occurs as a consequence of, or is caused by, another primary condition, event, or factor.
  • B. secondaryHub
    Indicates that an entity functions as a secondary or backup hub in relation to a primary hub within a network or system.
  • C. secondaryMissionField chosen
    Indicates a secondary or supporting operational area or objective associated with the primary mission.
  • D. secondaryFunction
    Indicates that an entity has an additional, supporting role or purpose beyond its primary function.
  • E. secondaryActivity
    Indicates that an entity engages in an additional, non-primary activity or role alongside its main activity.
  • F. None of above.

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_69ca835645e881908f00e3c8b51da81d completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc58fa0a208190a520e0e1f7faaea9 completed March 31, 2026, 11:30 p.m.
PD Predicate disambiguation batch_69cc456bda508190a9aa0fb92760739e completed March 31, 2026, 10:06 p.m.
Created at: March 30, 2026, 6:34 p.m.