Triple

T4608917
Position Surface form Disambiguated ID Type / Status
Subject Kamensky E100505 entity
Predicate hasVariant P455 FINISHED
Object Kamenskiy
Kamenskiy is a Slavic surname, commonly transliterated from Russian or related languages, borne by various individuals across Eastern Europe and the former Soviet Union.
 E483972 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: Kamenskiy | Statement: [Kamensky, hasVariant, Kamenskiy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kamenskiy
Context triple: [Kamensky, hasVariant, Kamenskiy]
  • A. Vyazemsky
    Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
  • B. Kuntsevskaya
    Kuntsevskaya is a Moscow Metro station on the Big Circle Line serving the Kuntsevo District in western Moscow.
  • C. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • D. Karamyshevskaya
    Karamyshevskaya is a metro station on Moscow’s Big Circle Line, serving the Khoroshyovo-Mnyovniki area of the city.
  • E. Paveletskaya
    Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
  • 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: Kamenskiy
Triple: [Kamensky, hasVariant, Kamenskiy]
Generated description
Kamenskiy is a Slavic surname, commonly transliterated from Russian or related languages, borne by various individuals across Eastern Europe and the former Soviet Union.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kamenskiy
Target entity description: Kamenskiy is a Slavic surname, commonly transliterated from Russian or related languages, borne by various individuals across Eastern Europe and the former Soviet Union.
  • A. Vyazemsky
    Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
  • B. Kuntsevskaya
    Kuntsevskaya is a Moscow Metro station on the Big Circle Line serving the Kuntsevo District in western Moscow.
  • C. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • D. Karamyshevskaya
    Karamyshevskaya is a metro station on Moscow’s Big Circle Line, serving the Khoroshyovo-Mnyovniki area of the city.
  • E. Paveletskaya
    Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
  • 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_69bd43cce1e08190a07d53af6a9b6c24 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd599f08d88190ad4bed8bafb592cd completed March 20, 2026, 2:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69be89c2485881908797f4a3560a0b04 completed March 21, 2026, 12:06 p.m.
NEDg Description generation batch_69be8aaa3eac8190876fc8c892cb7c3f completed March 21, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_69be8b164c8c8190b03e7e4892b6aa9e completed March 21, 2026, 12:12 p.m.
Created at: March 20, 2026, 1:12 p.m.