Triple

T4058083
Position Surface form Disambiguated ID Type / Status
Subject Liptov E84742 entity
Predicate hasRiver P165 FINISHED
Object Demänovka
Demänovka is a river in the Liptov region of northern Slovakia, known for flowing through the Demänovská Valley in the Low Tatras.
 E411852 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: Demänovka | Statement: [Liptov, hasRiver, Demänovka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Demänovka
Context triple: [Liptov, hasRiver, Demänovka]
  • A. Duleevka
    Duleevka is a small settlement in Russia known primarily as the birthplace of Soviet statesman Nikolai Ryzhkov.
  • B. Yanovka
    Yanovka is a small rural settlement in what is now Ukraine, historically part of the Russian Empire, best known as the birthplace of revolutionary leader Leon Trotsky.
  • C. Makiyivka
    Makiyivka is a major industrial city in eastern Ukraine’s Donetsk region, historically known for its coal mining and heavy industry.
  • D. Voykovskaya
    Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
  • E. Dobryninskaya
    Dobryninskaya is a Moscow Metro station on the circular Koltsevaya Line, known for its Stalinist-era architecture and central location.
  • 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: Demänovka
Triple: [Liptov, hasRiver, Demänovka]
Generated description
Demänovka is a river in the Liptov region of northern Slovakia, known for flowing through the Demänovská Valley in the Low Tatras.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Demänovka
Target entity description: Demänovka is a river in the Liptov region of northern Slovakia, known for flowing through the Demänovská Valley in the Low Tatras.
  • A. Duleevka
    Duleevka is a small settlement in Russia known primarily as the birthplace of Soviet statesman Nikolai Ryzhkov.
  • B. Yanovka
    Yanovka is a small rural settlement in what is now Ukraine, historically part of the Russian Empire, best known as the birthplace of revolutionary leader Leon Trotsky.
  • C. Makiyivka
    Makiyivka is a major industrial city in eastern Ukraine’s Donetsk region, historically known for its coal mining and heavy industry.
  • D. Voykovskaya
    Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
  • E. Dobryninskaya
    Dobryninskaya is a Moscow Metro station on the circular Koltsevaya Line, known for its Stalinist-era architecture and central location.
  • 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_69aed933bec881909edfa28ebb69c634 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefbaefcb081908aab3963dcd61a20 completed March 9, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562a6250081908f289f43b066b04d completed March 14, 2026, 1:29 p.m.
NEDg Description generation batch_69b563b3db0481909f3dd2a9e6a88e6e completed March 14, 2026, 1:33 p.m.
NED2 Entity disambiguation (via description) batch_69b567e223cc8190aa1d7e827e6c70fd completed March 14, 2026, 1:51 p.m.
Created at: March 9, 2026, 3:38 p.m.