Triple

T4549884
Position Surface form Disambiguated ID Type / Status
Subject Donetsk E110135 entity
Predicate formerName P65 FINISHED
Object Yuzovka
Yuzovka was the original name of the industrial settlement in eastern Ukraine that later developed into the city of Donetsk.
 E481821 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: Yuzovka | Statement: [Donetsk, formerName, Yuzovka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yuzovka
Context triple: [Donetsk, formerName, Yuzovka]
  • A. Kastornoye
    Kastornoye is a locality in Russia historically notable as the namesake and focal area of the Voronezh–Kastornoye military offensive during World War II.
  • B. Yuryev
    Yuryev is a historical name for the Estonian city now known as Tartu, reflecting its past under various regional powers.
  • C. Skovorodino
    Skovorodino is a small town in Russia’s Far Eastern Amur Oblast, known historically as a railway junction on the Trans-Siberian Railway.
  • D. Ostashkov
    Ostashkov is a historic town in western Russia situated on the shores of Lake Seliger, known as a local tourist and pilgrimage center.
  • E. Nikolskoye
    Nikolskoye is a town in northwestern Russia known as part of the Saint Petersburg metropolitan area in Leningrad 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: Yuzovka
Triple: [Donetsk, formerName, Yuzovka]
Generated description
Yuzovka was the original name of the industrial settlement in eastern Ukraine that later developed into the city of Donetsk.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Yuzovka
Target entity description: Yuzovka was the original name of the industrial settlement in eastern Ukraine that later developed into the city of Donetsk.
  • A. Kastornoye
    Kastornoye is a locality in Russia historically notable as the namesake and focal area of the Voronezh–Kastornoye military offensive during World War II.
  • B. Yuryev
    Yuryev is a historical name for the Estonian city now known as Tartu, reflecting its past under various regional powers.
  • C. Skovorodino
    Skovorodino is a small town in Russia’s Far Eastern Amur Oblast, known historically as a railway junction on the Trans-Siberian Railway.
  • D. Ostashkov
    Ostashkov is a historic town in western Russia situated on the shores of Lake Seliger, known as a local tourist and pilgrimage center.
  • E. Nikolskoye
    Nikolskoye is a town in northwestern Russia known as part of the Saint Petersburg metropolitan area in Leningrad 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_69bd4412524c8190be5bcc9ddee91848 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57f3f8348190868e274ac4df87ce completed March 20, 2026, 2:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69be777f287c81909f700e22163ccc24 completed March 21, 2026, 10:48 a.m.
NEDg Description generation batch_69be7b680ec08190957346de5c5acfa9 completed March 21, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69be7bbeda508190ae27ab12c6748ed7 completed March 21, 2026, 11:06 a.m.
Created at: March 20, 2026, 1:05 p.m.