Triple

T38468054
Position Surface form Disambiguated ID Type / Status
Subject Woodland, Wisconsin E912628 entity
Predicate isInCountryLevel P117234 FINISHED
Object United States NE NERFINISHED

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: United States | Statement: [Woodland, Wisconsin, isInCountryLevel, United States]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: isInCountryLevel
Context triple: [Woodland, Wisconsin, isInCountryLevel, United States]
  • A. isSetInCountry chosen
    Indicates that something (such as an event, story, or scene) takes place within the geographical or political boundaries of a specified country.
  • B. isInCountryISO
    Indicates that one entity is located within, or belongs to, the country identified by a specific ISO country code.
  • C. meetsInCountrySubdivision
    Indicates that two or more entities meet or have a meeting within a specific administrative subdivision of a country (such as a state, province, or region).
  • D. isWithinSingleCountry
    Indicates that all referenced locations lie inside the borders of the same country.
  • E. hasCountrySubdivisionLevel
    Indicates the hierarchical administrative level or tier at which a given country subdivision (such as a state, province, or region) is defined within the country's overall territorial organization.
  • 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_69f76e861d8c81908559031dc66e3c15 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcd313e61c8190b174b331365b803f completed May 7, 2026, 5:59 p.m.
PD Predicate disambiguation batch_69fcd1f6b2e08190bf0300ae7c9ae67a completed May 7, 2026, 5:55 p.m.
Created at: May 3, 2026, 4:31 p.m.