Triple

T17265744
Position Surface form Disambiguated ID Type / Status
Subject Обь E419121 entity
Predicate имеетПриток P94832 FINISHED
Object Вах
Вах — река в Западной Сибири России, протекающая по территории Ханты-Мансийского автономного округа и известная как один из значимых водных путей региона.
E1259996 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: Вах | Statement: [Обь, имеетПриток, Вах]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Вах
Context triple: [Обь, имеетПриток, Вах]
  • A. Vago
    Vago is a surname most notably associated with Pierre Vago, a prominent 20th-century French architect and influential figure in modern architecture.
  • B. Vorokhta
    Vorokhta is a Ukrainian mountain resort village in the Carpathians, known as a gateway for hiking and skiing in the Hoverla and Chornohora ranges.
  • C. Varsham
    Varsham is a 2004 Telugu romantic action film that significantly boosted actor Prabhas's popularity in the Indian film industry.
  • D. Vyazhan
    Vyazhan is the Tamil calendar day associated with the planet Jupiter and traditionally linked to Thursday.
  • E. Vasishka
    Vasishka was a Kushan emperor who ruled parts of northern India and Central Asia in the early 3rd century CE, known primarily from his inscriptions and coinage.
  • 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: Вах
Triple: [Обь, имеетПриток, Вах]
Generated description
Вах — река в Западной Сибири России, протекающая по территории Ханты-Мансийского автономного округа и известная как один из значимых водных путей региона.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Вах
Target entity description: Вах — река в Западной Сибири России, протекающая по территории Ханты-Мансийского автономного округа и известная как один из значимых водных путей региона.
  • A. Vago
    Vago is a surname most notably associated with Pierre Vago, a prominent 20th-century French architect and influential figure in modern architecture.
  • B. Vorokhta
    Vorokhta is a Ukrainian mountain resort village in the Carpathians, known as a gateway for hiking and skiing in the Hoverla and Chornohora ranges.
  • C. Varsham
    Varsham is a 2004 Telugu romantic action film that significantly boosted actor Prabhas's popularity in the Indian film industry.
  • D. Vyazhan
    Vyazhan is the Tamil calendar day associated with the planet Jupiter and traditionally linked to Thursday.
  • E. Vasishka
    Vasishka was a Kushan emperor who ruled parts of northern India and Central Asia in the early 3rd century CE, known primarily from his inscriptions and coinage.
  • 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_69d886d9ab108190b70edd8d17aa1204 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42f44ec7c81909a925fc8692b0a6c completed April 19, 2026, 1:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01794641648190a5db87ecb359c17a completed May 11, 2026, 6:37 a.m.
NEDg Description generation batch_6a017abddcc48190872f77b62ac9896e completed May 11, 2026, 6:44 a.m.
NED2 Entity disambiguation (via description) batch_6a017b7e72908190913215717fb04b0f completed May 11, 2026, 6:47 a.m.
Created at: April 10, 2026, 5:40 a.m.