Triple

T30554359
Position Surface form Disambiguated ID Type / Status
Subject Capital Nacional do Caminhão E777653 entity
Predicate appliesToMunicipalityType P10835 FINISHED
Object municipality 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: municipality | Statement: [Capital Nacional do Caminhão, appliesToMunicipalityType, municipality]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: appliesToMunicipalityType
Context triple: [Capital Nacional do Caminhão, appliesToMunicipalityType, municipality]
  • A. hasMunicipalityType chosen
    Indicates that an administrative unit is classified as having a specific type or category of municipality (e.g., city, town, village).
  • B. isPartOfMunicipalityType
    Indicates that one administrative unit or area belongs to, or is classified under, a specific type or category of municipality.
  • C. isInMunicipality
    Indicates that one entity (typically a place or address) is located within the administrative boundaries of a specific municipality.
  • D. affectsMunicipality
    Indicates that one entity has an impact on, influences, or brings about changes in a specific municipality.
  • E. appliesToUrbanAreaType
    Indicates that something (such as a rule, measure, or classification) is applicable specifically to a particular type or category of urban area.
  • 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_69f2249e19108190a458ab446096bf22 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69fdd92396788190ae1424bc1ae55844 completed May 8, 2026, 12:37 p.m.
PD Predicate disambiguation batch_69fdd678f40481909a717a2daec83b36 completed May 8, 2026, 12:26 p.m.
Created at: April 29, 2026, 8:20 p.m.