Triple

T34113506
Position Surface form Disambiguated ID Type / Status
Subject Nagorny District E874902 entity
Predicate belongsToFederalSubject P199531 FINISHED
Object Moscow 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: Moscow | Statement: [Nagorny District, belongsToFederalSubject, Moscow]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: belongsToFederalSubject
Context triple: [Nagorny District, belongsToFederalSubject, Moscow]
  • A. containsFederalSubject
    Indicates that one administrative or territorial entity includes a specific federal subject within its jurisdiction or boundaries.
  • B. federalSubject
    Indicates that one entity is a federal subject (a primary administrative or constituent unit) of the other entity, typically a sovereign state or federation.
  • C. belongsToNationState
    Indicates that an entity is a member, part, or constituent of a specific nation-state, reflecting a formal or recognized association with that country.
  • D. stateFederationAffiliation
    Indicates that a state is formally affiliated with, or a member of, a particular federation or federal entity.
  • E. usedInFederalSubject
    Indicates that something (such as a law, standard, or resource) is applied, implemented, or in effect within a specific federal subject (administrative region) of a country.
  • 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_69f349a80d4481908527317d43f5c579 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69ff409ff5548190849c2d50e99bd807 completed May 9, 2026, 2:11 p.m.
PD Predicate disambiguation batch_69ff401a5e188190a72f945e910b4a6c completed May 9, 2026, 2:09 p.m.
PDg Predicate description generation batch_69ff409ee6ec819088b7c13fabed2ac2 completed May 9, 2026, 2:11 p.m.
Created at: May 1, 2026, 1:53 a.m.