Triple

T3331952
Position Surface form Disambiguated ID Type / Status
Subject Khabarovsk Krai E70051 entity
Predicate hasPart P35 FINISHED
Object Vyazemsky
Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
 E350563 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: Vyazemsky | Statement: [Khabarovsk Krai, hasPart, Vyazemsky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vyazemsky
Context triple: [Khabarovsk Krai, hasPart, Vyazemsky]
  • A. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • B. Vorontsovskaya
    Vorontsovskaya is a metro station on Moscow’s Big Circle Line serving the southwestern part of the city.
  • C. Kuntsevskaya
    Kuntsevskaya is a Moscow Metro station on the Big Circle Line serving the Kuntsevo District in western Moscow.
  • D. Voykovskaya
    Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
  • E. Vyatka
    Vyatka was a historic region and town in northeastern European Russia, known as a frontier area that was gradually incorporated into the centralized Russian state.
  • 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: Vyazemsky
Triple: [Khabarovsk Krai, hasPart, Vyazemsky]
Generated description
Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vyazemsky
Target entity description: Vyazemsky is a small town in Russia’s Far Eastern Federal District, serving as an administrative center within Khabarovsk Krai.
  • A. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • B. Vorontsovskaya
    Vorontsovskaya is a metro station on Moscow’s Big Circle Line serving the southwestern part of the city.
  • C. Kuntsevskaya
    Kuntsevskaya is a Moscow Metro station on the Big Circle Line serving the Kuntsevo District in western Moscow.
  • D. Voykovskaya
    Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
  • E. Vyatka
    Vyatka was a historic region and town in northeastern European Russia, known as a frontier area that was gradually incorporated into the centralized Russian state.
  • 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb19358e48190a503af01b92273a4 completed March 8, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b32514c2f48190b20b8975c96d32a7 completed March 12, 2026, 8:41 p.m.
NEDg Description generation batch_69b3264fee388190a693ecf748074f04 completed March 12, 2026, 8:47 p.m.
NED2 Entity disambiguation (via description) batch_69b326af5e1481908930410ce9be1339 completed March 12, 2026, 8:48 p.m.
Created at: March 8, 2026, 3:12 p.m.