Triple

T14074086
Position Surface form Disambiguated ID Type / Status
Subject Rupert E338685 entity
Predicate hasStateLevel P84299 FINISHED
Object subject to the government of West Virginia 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: subject to the government of West Virginia | Statement: [Rupert, hasStateLevel, subject to the government of West Virginia]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasStateLevel
Context triple: [Rupert, hasStateLevel, subject to the government of West Virginia]
  • A. hasStateOrDistrict chosen
    Indicates that an entity is associated with, located in, or belongs to a particular state or district.
  • B. stateLevelStrength
    Indicates the degree of power, capacity, or effectiveness that a state-level entity possesses in performing its functions or exerting influence.
  • C. hasProvinceStatus
    Indicates that an entity holds the administrative or political status of a province within a larger territorial or governmental system.
  • D. hasMunicipalLevel
    Indicates that an entity is associated with a specific level or tier within a municipal (local government) hierarchy.
  • E. hasProvinceLevelUnit
    Indicates that one administrative or territorial entity possesses or contains a sub-unit at the province (or equivalent) level.
  • 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_69d81c687b0c819087fd9ed4198403f8 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5c5bc49881909012b66fa451f495 completed April 14, 2026, 3:25 p.m.
PD Predicate disambiguation batch_69de05b0e6c88190a819eeba0028981f completed April 14, 2026, 9:15 a.m.
Created at: April 9, 2026, 10:21 p.m.