Triple

T3449648
Position Surface form Disambiguated ID Type / Status
Subject Dzyarzhynskaya Hara E72761 entity
Predicate hasLanguageForm P6281 FINISHED
Object Russian name "Гора Дзержинская"
"Гора Дзержинская" is the Russian name for Dzyarzhynskaya Hara, the highest natural point in Belarus.
 E358186 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: Russian name "Гора Дзержинская" | Statement: [Dzyarzhynskaya Hara, hasLanguageForm, Russian name "Гора Дзержинская"]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Russian name "Гора Дзержинская"
Context triple: [Dzyarzhynskaya Hara, hasLanguageForm, Russian name "Гора Дзержинская"]
  • A. Khoroshevskaya
    Khoroshevskaya is a Moscow Metro station located on the Big Circle Line, serving the Khoroshyovsky District of the city.
  • B. Dzerzhinsk
    Dzerzhinsk is a major industrial city in western Russia known for its large chemical manufacturing sector and associated environmental issues.
  • C. Kantemirovskaya
    Kantemirovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the southern part of the city.
  • D. Mount Narodnaya
    Mount Narodnaya is a prominent peak in Russia known as the tallest mountain in the Ural range, marking the natural boundary between Europe and Asia.
  • E. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • 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: Russian name "Гора Дзержинская"
Triple: [Dzyarzhynskaya Hara, hasLanguageForm, Russian name "Гора Дзержинская"]
Generated description
"Гора Дзержинская" is the Russian name for Dzyarzhynskaya Hara, the highest natural point in Belarus.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Russian name "Гора Дзержинская"
Target entity description: "Гора Дзержинская" is the Russian name for Dzyarzhynskaya Hara, the highest natural point in Belarus.
  • A. Khoroshevskaya
    Khoroshevskaya is a Moscow Metro station located on the Big Circle Line, serving the Khoroshyovsky District of the city.
  • B. Dzerzhinsk
    Dzerzhinsk is a major industrial city in western Russia known for its large chemical manufacturing sector and associated environmental issues.
  • C. Kantemirovskaya
    Kantemirovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the southern part of the city.
  • D. Mount Narodnaya
    Mount Narodnaya is a prominent peak in Russia known as the tallest mountain in the Ural range, marking the natural boundary between Europe and Asia.
  • E. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • 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_69ad85b05c848190b7a28ceec2bd7b74 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adba71f4a4819089d08b871cc9b16f completed March 8, 2026, 6:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360eb7ad08190865e62228365d530 completed March 13, 2026, 12:57 a.m.
NEDg Description generation batch_69b3616dec3881908a54fa6500f7efb0 completed March 13, 2026, 12:59 a.m.
NED2 Entity disambiguation (via description) batch_69b36211b6b08190ac0cac646160495d completed March 13, 2026, 1:02 a.m.
Created at: March 8, 2026, 3:16 p.m.