Triple

T10284101
Position Surface form Disambiguated ID Type / Status
Subject Rivne Oblast E241181 entity
Predicate contains P35 FINISHED
Object Varash
Varash is a city in western Ukraine known for hosting the Rivne Nuclear Power Plant and serving as an important industrial and energy center in Rivne Oblast.
E852611 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: Varash | Statement: [Rivne Oblast, contains, Varash]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Varash
Context triple: [Rivne Oblast, contains, Varash]
  • A. Varsham
    Varsham is a 2004 Telugu romantic action film that significantly boosted actor Prabhas's popularity in the Indian film industry.
  • B. Gori
    Gori is a city in central Georgia best known as the birthplace of Soviet leader Joseph Stalin.
  • C. Vashi
    Vashi is a major suburban railway station and commercial-residential hub in Navi Mumbai, India.
  • D. Varamin
    Varamin is a historic city in northern Iran, known for its agricultural importance and notable Islamic architecture, including the Jameh Mosque of Varamin.
  • E. Durov
    Durov is a Russian surname most prominently associated with Pavel Durov, the entrepreneur and founder of the social networking site VKontakte and the messaging app Telegram.
  • 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: Varash
Triple: [Rivne Oblast, contains, Varash]
Generated description
Varash is a city in western Ukraine known for hosting the Rivne Nuclear Power Plant and serving as an important industrial and energy center in Rivne Oblast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Varash
Target entity description: Varash is a city in western Ukraine known for hosting the Rivne Nuclear Power Plant and serving as an important industrial and energy center in Rivne Oblast.
  • A. Varsham
    Varsham is a 2004 Telugu romantic action film that significantly boosted actor Prabhas's popularity in the Indian film industry.
  • B. Gori
    Gori is a city in central Georgia best known as the birthplace of Soviet leader Joseph Stalin.
  • C. Vashi
    Vashi is a major suburban railway station and commercial-residential hub in Navi Mumbai, India.
  • D. Varamin
    Varamin is a historic city in northern Iran, known for its agricultural importance and notable Islamic architecture, including the Jameh Mosque of Varamin.
  • E. Durov
    Durov is a Russian surname most prominently associated with Pavel Durov, the entrepreneur and founder of the social networking site VKontakte and the messaging app Telegram.
  • 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.