Triple

T17709813
Position Surface form Disambiguated ID Type / Status
Subject Syretsko–Pecherska line E441532 entity
Predicate hasStation P35 FINISHED
Object Kharkivska
Kharkivska is a metro station on the Kyiv Metro system in Ukraine.
E1297764 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: Kharkivska | Statement: [Syretsko–Pecherska line, hasStation, Kharkivska]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kharkivska
Context triple: [Syretsko–Pecherska line, hasStation, Kharkivska]
  • A. Oleksandriia
    Oleksandriia is a city in central Ukraine known as an industrial and transport hub within the Kirovohrad region.
  • B. Kremenchuk
    Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
  • C. Kharkiv
    Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
  • D. Chernihiv
    Chernihiv is a historic city in northern Ukraine known for its ancient churches, rich cultural heritage, and role as a regional administrative and memorial center.
  • E. Kropyvnytskyi
    Kropyvnytskyi is a regional city in central Ukraine known as an important administrative, cultural, and transportation center.
  • 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: Kharkivska
Triple: [Syretsko–Pecherska line, hasStation, Kharkivska]
Generated description
Kharkivska is a metro station on the Kyiv Metro system in Ukraine.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kharkivska
Target entity description: Kharkivska is a metro station on the Kyiv Metro system in Ukraine.
  • A. Oleksandriia
    Oleksandriia is a city in central Ukraine known as an industrial and transport hub within the Kirovohrad region.
  • B. Kremenchuk
    Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
  • C. Kharkiv
    Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
  • D. Chernihiv
    Chernihiv is a historic city in northern Ukraine known for its ancient churches, rich cultural heritage, and role as a regional administrative and memorial center.
  • E. Kropyvnytskyi
    Kropyvnytskyi is a regional city in central Ukraine known as an important administrative, cultural, and transportation center.
  • 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_69d8b9ea20b48190ace88bb46b01e6a9 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4729a9a9c81908d65ff0bda12c961 completed April 19, 2026, 6:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0328ff60388190af4f7fe30a4c1d7c completed May 12, 2026, 1:19 p.m.
NEDg Description generation batch_6a032b79b55c81909ad92206c44402f5 completed May 12, 2026, 1:30 p.m.
NED2 Entity disambiguation (via description) batch_6a032c1200808190982b03ba82dda8cb completed May 12, 2026, 1:33 p.m.
Created at: April 10, 2026, 10:05 a.m.