Triple

T3609785
Position Surface form Disambiguated ID Type / Status
Subject Mount Vernon, New York E76456 entity
Predicate hasPopulationRankInCounty P24333 FINISHED
Object one of the largest cities in Westchester County 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: one of the largest cities in Westchester County | Statement: [Mount Vernon, New York, hasPopulationRankInCounty, one of the largest cities in Westchester County]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPopulationRankInCounty
Context triple: [Mount Vernon, New York, hasPopulationRankInCounty, one of the largest cities in Westchester County]
  • A. populationRankInCounty chosen
    Indicates the relative position of an entity in terms of population size compared to other entities within the same county.
  • B. hasPopulationRank
    Indicates the relative position of an entity in an ordered list based on the size of its population.
  • C. mostPopulousCountyIn
    Indicates that the subject is the county with the largest population within the specified object region or jurisdiction.
  • D. hasPopulationRankInRegion
    Indicates that an entity has a specific population-based rank or position within a defined geographic region.
  • E. rankByPopulationInUnitedStates
    Indicates the relative ordering of entities based on their population size within the United States.
  • 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_69ad85da0ba481908b3b48c69efe2b98 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc22b824c8190a85b36185d4957bb completed March 8, 2026, 6:38 p.m.
PD Predicate disambiguation batch_69adb83d8b1c8190b3bddbc5dc995a87 completed March 8, 2026, 5:56 p.m.
Created at: March 8, 2026, 3:23 p.m.