Triple

T12664700
Position Surface form Disambiguated ID Type / Status
Subject Votkinsk E302516 entity
Predicate namedInLanguage P15 FINISHED
Object Воткинск
Воткинск — это промышленный город в Удмуртской Республике России, известный как родина композитора Петра Чайковского и центр машиностроения.
 E1083381 NE FINISHED

How this triple was built (4 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: Воткинск | Statement: [Votkinsk, namedInLanguage, Воткинск]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Воткинск
Context triple: [Votkinsk, namedInLanguage, Воткинск]
  • A. Volokolamsk
    Volokolamsk is a historic town in western Russia, located northwest of Moscow and known for its medieval origins and role in regional trade and defense.
  • B. Lipetsk
    Lipetsk is a major industrial city in western Russia, known for its steel production and status as the administrative center of Lipetsk Oblast.
  • C. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
  • D. Penza
    Penza is a city in western Russia known as a regional cultural and industrial center.
  • E. 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.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Воткинск
Triple: [Votkinsk, namedInLanguage, Воткинск]
Generated description
Воткинск — это промышленный город в Удмуртской Республике России, известный как родина композитора Петра Чайковского и центр машиностроения.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Воткинск
Target entity description: Воткинск — это промышленный город в Удмуртской Республике России, известный как родина композитора Петра Чайковского и центр машиностроения.
  • A. Volokolamsk
    Volokolamsk is a historic town in western Russia, located northwest of Moscow and known for its medieval origins and role in regional trade and defense.
  • B. Lipetsk
    Lipetsk is a major industrial city in western Russia, known for its steel production and status as the administrative center of Lipetsk Oblast.
  • C. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
  • D. Penza
    Penza is a city in western Russia known as a regional cultural and industrial center.
  • E. 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.
  • 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9617e030881908444743b8a7e0d75 completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf7cb4d348190962ba5fa21fbb77b completed May 7, 2026, 8:36 p.m.
NEDg Description generation batch_69fd02e0fcc081909349dbe0d14f38ba completed May 7, 2026, 9:23 p.m.
NED2 Entity disambiguation (via description) batch_69fd035441d8819084635cea48a163df completed May 7, 2026, 9:25 p.m.
Created at: April 9, 2026, 5:19 p.m.