Triple

T769082
Position Surface form Disambiguated ID Type / Status
Subject KSFO E16239 entity
Predicate hasCountryCodeRegion P3446 FINISHED
Object US-CA E26 NE FINISHED

How this triple was built (3 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: US-CA | Statement: [KSFO, hasCountryCodeRegion, US-CA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: US-CA
Context triple: [KSFO, hasCountryCodeRegion, US-CA]
  • A. California, United States chosen
    California, United States is a large and populous U.S. state on the West Coast known for its diverse geography, major technology and entertainment industries, and cultural and economic influence.
  • B. CA
    CA is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Canada in international standards and systems.
  • C. California, Pennsylvania
    California, Pennsylvania is a small borough in southwestern Pennsylvania best known as the home of PennWest California (formerly California University of Pennsylvania) along the Monongahela River.
  • D. US
    US is the IATA airline designator code assigned to the former American airline US Airways.
  • E. Ontario, California
    Ontario, California is a mid-sized Inland Empire city in San Bernardino County known for its major international airport, logistics hubs, and role as a regional commercial center in Southern California.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCountryCodeRegion
Context triple: [KSFO, hasCountryCodeRegion, US-CA]
  • A. hasRegionCode chosen
    Indicates that an entity is associated with a specific regional identifier or code.
  • B. regionCodeType
    Indicates the classification or format type used for a given region code within a coding or identification system.
  • C. countryOrRegion
    Indicates that one entity is a country or geographic region associated with another entity (such as its location, jurisdiction, or area of relevance).
  • D. countryRegion
    Indicates that a country is located within, or belongs to, a specific geographic or administrative region.
  • E. hasRegion
    Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
  • F. None of above.

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_69a49369a0848190af883934cee3db4c completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a70376988190be2826259f5281ab completed March 1, 2026, 8:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc5f8bc2081908f7d2435ce43fdc4 completed March 8, 2026, 12:42 a.m.
PD Predicate disambiguation batch_69a4a508c42c8190850a0ac7844a3ea9 completed March 1, 2026, 8:43 p.m.
Created at: March 1, 2026, 7:37 p.m.