Triple

T8269307
Position Surface form Disambiguated ID Type / Status
Subject Lesya Ukrainka E193381 entity
Predicate residence P75 FINISHED
Object Kolodiazhne
Kolodiazhne is a village in northwestern Ukraine known for being closely associated with the life and creative work of the renowned poet Lesya Ukrainka.
 E731118 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: Kolodiazhne | Statement: [Lesya Ukrainka, residence, Kolodiazhne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kolodiazhne
Context triple: [Lesya Ukrainka, residence, Kolodiazhne]
  • A. Pryluky
    Pryluky is a historic city in northern Ukraine known for its Cossack heritage and role as a regional cultural and economic center.
  • B. Dzyarzhynsk
    Dzyarzhynsk is a town in Belarus known for its proximity to Dzyarzhynskaya Hara, the country’s highest point.
  • C. Kremenets
    Kremenets is a historic town in western Ukraine known for its rich cultural heritage and once-significant Jewish community.
  • D. Lokhvytsia
    Lokhvytsia is a town in central Ukraine, historically part of the Poltava region and known for its role in regional trade and agriculture.
  • E. Zhmerynka
    Zhmerynka is a city in central Ukraine known as an important regional railway junction and administrative 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: Kolodiazhne
Triple: [Lesya Ukrainka, residence, Kolodiazhne]
Generated description
Kolodiazhne is a village in northwestern Ukraine known for being closely associated with the life and creative work of the renowned poet Lesya Ukrainka.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kolodiazhne
Target entity description: Kolodiazhne is a village in northwestern Ukraine known for being closely associated with the life and creative work of the renowned poet Lesya Ukrainka.
  • A. Pryluky
    Pryluky is a historic city in northern Ukraine known for its Cossack heritage and role as a regional cultural and economic center.
  • B. Dzyarzhynsk
    Dzyarzhynsk is a town in Belarus known for its proximity to Dzyarzhynskaya Hara, the country’s highest point.
  • C. Kremenets
    Kremenets is a historic town in western Ukraine known for its rich cultural heritage and once-significant Jewish community.
  • D. Lokhvytsia
    Lokhvytsia is a town in central Ukraine, historically part of the Poltava region and known for its role in regional trade and agriculture.
  • E. Zhmerynka
    Zhmerynka is a city in central Ukraine known as an important regional railway junction and administrative 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_69ca82e14ae481908ffdb822cd2192bc completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb795127ac81908196008f5579f83f completed March 31, 2026, 7:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce025db14881909124c1398d5f7d4a completed April 2, 2026, 5:45 a.m.
NEDg Description generation batch_69ce077d8af0819082a7ea67a2c11ddd completed April 2, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_69ce082078108190867044f45bc0a806 completed April 2, 2026, 6:09 a.m.
Created at: March 30, 2026, 5:50 p.m.