Triple

T21349256
Position Surface form Disambiguated ID Type / Status
Subject Kuznetsk E526428 entity
Predicate roadConnection P385 FINISHED
Object Penza 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: Penza | Statement: [Kuznetsk, roadConnection, Penza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Penza
Context triple: [Kuznetsk, roadConnection, Penza]
  • A. Penza chosen
    Penza is a city in western Russia known as a regional cultural and industrial center.
  • B. Izhevsk
    Izhevsk is a major industrial city in western Russia, best known as a center of arms manufacturing and the capital of the Udmurt Republic.
  • C. Lipetsk
    Lipetsk is a major industrial city in western Russia, known for its steel production and status as the administrative center of Lipetsk Oblast.
  • D. Tambov
    Tambov is a city in western Russia known as an administrative, cultural, and industrial center of the Tambov Oblast.
  • E. Ulyanovsk
    Ulyanovsk is a city in western Russia on the Volga River, best known as the birthplace of Vladimir Lenin and an important regional industrial and cultural center.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51cd5cc81909ac1187971e8a8ad completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee5bab98148190aa14d52fd37bc894 completed April 26, 2026, 6:38 p.m.
Created at: April 16, 2026, 5:02 p.m.