Triple

T10284103
Position Surface form Disambiguated ID Type / Status
Subject Rivne Oblast E241181 entity
Predicate contains P35 FINISHED
Object Zdolbuniv
Zdolbuniv is a small city in western Ukraine known historically as a local railway hub and administrative center.
E852613 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: Zdolbuniv | Statement: [Rivne Oblast, contains, Zdolbuniv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zdolbuniv
Context triple: [Rivne Oblast, contains, Zdolbuniv]
  • A. Zenkiv
    Zenkiv is a historic town in central Ukraine, known for its role as a local administrative and cultural center in the Poltava region.
  • B. Shpola
    Shpola is a small town in central Ukraine that serves as an administrative center within Cherkasy Oblast.
  • C. Kahuta
    Kahuta is a town in Pakistan’s Punjab province known for hosting the country’s primary nuclear research and enrichment facilities.
  • D. Vynohradiv
    Vynohradiv is a town in western Ukraine’s Zakarpattia Oblast, known for its historical architecture and location near the Hungarian and Romanian borders.
  • E. Livny
    Livny is a historic town in western Russia known as one of the principal urban centers of Oryol Oblast.
  • 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: Zdolbuniv
Triple: [Rivne Oblast, contains, Zdolbuniv]
Generated description
Zdolbuniv is a small city in western Ukraine known historically as a local railway hub and administrative center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zdolbuniv
Target entity description: Zdolbuniv is a small city in western Ukraine known historically as a local railway hub and administrative center.
  • A. Zenkiv
    Zenkiv is a historic town in central Ukraine, known for its role as a local administrative and cultural center in the Poltava region.
  • B. Shpola
    Shpola is a small town in central Ukraine that serves as an administrative center within Cherkasy Oblast.
  • C. Kahuta
    Kahuta is a town in Pakistan’s Punjab province known for hosting the country’s primary nuclear research and enrichment facilities.
  • D. Vynohradiv
    Vynohradiv is a town in western Ukraine’s Zakarpattia Oblast, known for its historical architecture and location near the Hungarian and Romanian borders.
  • E. Livny
    Livny is a historic town in western Russia known as one of the principal urban centers of Oryol Oblast.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2b5853081909cd0397e08a0f44d completed April 7, 2026, 9:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f83c3c488190b728783bc260b006 completed April 9, 2026, 12:52 a.m.
NEDg Description generation batch_69d6fcae243c819095a2e791716805bd completed April 9, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_69d6fd3495fc8190a093d2536cfbe58a completed April 9, 2026, 1:13 a.m.
Created at: April 6, 2026, 11:39 a.m.