Triple

T1492349
Position Surface form Disambiguated ID Type / Status
Subject Russin E29607 entity
Predicate cantonCode P28599 FINISHED
Object GE E129065 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: GE | Statement: [Russin, cantonCode, GE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GE
Context triple: [Russin, cantonCode, GE]
  • A. GE
    GE is the ISO 3166-1 alpha-2 country code for Georgia, a nation at the crossroads of Eastern Europe and Western Asia.
  • B. GE chosen
    GE is the Swiss canton code for Geneva, a major city and canton in western Switzerland known for its international organizations and financial center.
  • C. General Electric
    General Electric is a major American multinational conglomerate historically known for its leadership in industrial manufacturing, aviation, power, and healthcare technologies.
  • D. General Motors
    General Motors is a major American multinational automotive manufacturer known for brands such as Chevrolet, GMC, Cadillac, and Buick.
  • E. Bosch
    Bosch is a multinational engineering and technology company best known for its automotive components, industrial products, and household appliances.
  • 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: cantonCode
Context triple: [Russin, cantonCode, GE]
  • A. hasCanton
    Indicates that an entity is administratively divided into, or associated with, a specific canton.
  • B. canton
    Indicates that an entity is administratively located within, belongs to, or is governed as part of a specific canton.
  • C. inseeCode
    Indicates the official INSEE (French national statistics institute) code assigned to an entity, typically identifying a specific geographic or administrative unit.
  • D. featuresCanton
    Indicates that an administrative region or entity includes or is associated with a specific canton as one of its subdivisions or components.
  • E. includesCanton
    Indicates that a larger administrative or geographic entity contains or encompasses a specific canton within its boundaries.
  • F. None of above. chosen

Provenance (5 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_69a498dba1d8819093b46a3a8d2485f1 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6c4f0c88190a97ba4910c1a5d85 completed March 1, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1ca98e64819097916eb7717e6364 completed March 8, 2026, 6:52 a.m.
PD Predicate disambiguation batch_69a4c48902808190a8028d359bcf123e completed March 1, 2026, 10:58 p.m.
PDg Predicate description generation batch_69a4c52c703c8190a56389b09d97659f completed March 1, 2026, 11:01 p.m.
Created at: March 1, 2026, 8:12 p.m.