Triple

T17506732
Position Surface form Disambiguated ID Type / Status
Subject Waterbury metropolitan area E426336 entity
Predicate statisticalAreaClass P55658 FINISHED
Object metropolitan area 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: metropolitan area | Statement: [Waterbury metropolitan area, statisticalAreaClass, metropolitan area]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: statisticalAreaClass
Context triple: [Waterbury metropolitan area, statisticalAreaClass, metropolitan area]
  • A. statisticalAreaClassification chosen
    Indicates how an area is categorized based on statistical criteria, such as population, density, or other quantitative measures, for analysis or reporting purposes.
  • B. statisticalAreaOf
    Indicates that one entity is the designated statistical area or region associated with, containing, or characterizing another entity for statistical or demographic purposes.
  • C. combinedStatisticalArea
    Indicates that two or more adjacent metropolitan or micropolitan areas are grouped together into a larger combined statistical region based on significant economic and social integration.
  • D. metropolitanStatisticalArea
    Indicates that one place is part of, or classified within, a specific metropolitan statistical area as defined for demographic or economic analysis.
  • E. urbanDistrictType
    Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
  • 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_69d889dd9164819087b1dc3c9240c870 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e45258b73c81909db581d4f1d27921 completed April 19, 2026, 3:56 a.m.
PD Predicate disambiguation batch_69e3b4f5fbcc8190a6ea9639bf5650da completed April 18, 2026, 4:44 p.m.
Created at: April 10, 2026, 5:48 a.m.