Triple

T4465619
Position Surface form Disambiguated ID Type / Status
Subject Kyiv Metro E98369 entity
Predicate hasStation P35 FINISHED
Object Chervonyi Khutir
Chervonyi Khutir is a metro station on the Kyiv Metro system in Ukraine.
E444194 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: Chervonyi Khutir | Statement: [Kyiv Metro, hasStation, Chervonyi Khutir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chervonyi Khutir
Context triple: [Kyiv Metro, hasStation, Chervonyi Khutir]
  • A. Zavrazhye
    Zavrazhye is a rural locality in Russia best known as the birthplace of renowned film director Andrei Tarkovsky.
  • B. Kremenets
    Kremenets is a historic town in western Ukraine known for its rich cultural heritage and once-significant Jewish community.
  • C. Ostriv Zmiinyi
    Ostriv Zmiinyi is a small but strategically important Ukrainian island in the Black Sea, widely known as Snake Island.
  • D. Horokhiv
    Horokhiv is a small town in western Ukraine known for its location within the historic Volyn region.
  • E. Horlivka
    Horlivka is an industrial city in eastern Ukraine’s Donetsk region, known for its coal mining and chemical industries and its location within the contested Donbas area.
  • 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: Chervonyi Khutir
Triple: [Kyiv Metro, hasStation, Chervonyi Khutir]
Generated description
Chervonyi Khutir is a metro station on the Kyiv Metro system in Ukraine.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Chervonyi Khutir
Target entity description: Chervonyi Khutir is a metro station on the Kyiv Metro system in Ukraine.
  • A. Zavrazhye
    Zavrazhye is a rural locality in Russia best known as the birthplace of renowned film director Andrei Tarkovsky.
  • B. Kremenets
    Kremenets is a historic town in western Ukraine known for its rich cultural heritage and once-significant Jewish community.
  • C. Ostriv Zmiinyi
    Ostriv Zmiinyi is a small but strategically important Ukrainian island in the Black Sea, widely known as Snake Island.
  • D. Horokhiv
    Horokhiv is a small town in western Ukraine known for its location within the historic Volyn region.
  • E. Horlivka
    Horlivka is an industrial city in eastern Ukraine’s Donetsk region, known for its coal mining and chemical industries and its location within the contested Donbas area.
  • 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_69b3454a7c608190944f5455c8031d73 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b356991a588190be2f95fd957d7f99 completed March 13, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6513446f08190b4ab18dffda9060a completed March 15, 2026, 6:27 a.m.
NEDg Description generation batch_69b651e8a92881909a835e5cad3d8cb9 completed March 15, 2026, 6:30 a.m.
NED2 Entity disambiguation (via description) batch_69b65259ccec8190a178e2d9930da0a8 completed March 15, 2026, 6:31 a.m.
Created at: March 12, 2026, 11:34 p.m.