Triple

T3889558
Position Surface form Disambiguated ID Type / Status
Subject Tucson, Arizona, United States E88025 entity
Predicate rankInArizonaByPopulation P51671 FINISHED
Object second-largest city in Arizona 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: second-largest city in Arizona | Statement: [Tucson, Arizona, United States, rankInArizonaByPopulation, second-largest city in Arizona]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: rankInArizonaByPopulation
Context triple: [Tucson, Arizona, United States, rankInArizonaByPopulation, second-largest city in Arizona]
  • A. rankInCaliforniaByPopulation
    Indicates the ordinal position of an entity in a list of California entities ordered by their population size.
  • B. rankByPopulationInUS
    Indicates the relative ordering of entities based on the size of their populations within the United States.
  • C. rankByPopulationInUnitedStates
    Indicates the relative ordering of entities based on their population size within the United States.
  • D. rankInKansasByPopulation
    Indicates the position of an entity in an ordered list of Kansas entities based on their population size.
  • E. rankByPopulationInColorado
    Indicates the relative ordering of entities based on their population size within the state of Colorado.
  • F. None of above. chosen

Provenance (4 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_69aed9466d548190939f5217a23ed4ac completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecaee7148190ada451ccfc6582ee completed March 9, 2026, 3:52 p.m.
PD Predicate disambiguation batch_69aee759609c8190985e96ec6d96dedd completed March 9, 2026, 3:29 p.m.
PDg Predicate description generation batch_69aee80858a481909961a33fb50ff8d1 completed March 9, 2026, 3:32 p.m.
Created at: March 9, 2026, 3:21 p.m.