Triple

T8011564
Position Surface form Disambiguated ID Type / Status
Subject Moscow Governorate E186504 entity
Predicate hasMajorCity P316 FINISHED
Object Yegoryevsk
Yegoryevsk is a historic town in Russia, now part of Moscow Oblast, known for its 19th-century architecture and industrial heritage.
E709144 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: Yegoryevsk | Statement: [Moscow Governorate, hasMajorCity, Yegoryevsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yegoryevsk
Context triple: [Moscow Governorate, hasMajorCity, Yegoryevsk]
  • A. Orekhovo
    Orekhovo is a Moscow Metro station on the Zamoskvoretskaya Line serving the Orekhovo-Borisovo district in southern Moscow.
  • B. Yuryev
    Yuryev is a historical name for the Estonian city now known as Tartu, reflecting its past under various regional powers.
  • C. Pleskov
    Pleskov is an alternative historical or variant name for the Russian city of Pskov, a historic regional center in northwestern Russia.
  • D. Petrovskoye
    Petrovskoye was the original Russian fortress settlement that later developed into the modern city of Makhachkala in Dagestan, Russia.
  • E. Yuzovka
    Yuzovka was the original name of the industrial settlement in eastern Ukraine that later developed into the city of Donetsk.
  • 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: Yegoryevsk
Triple: [Moscow Governorate, hasMajorCity, Yegoryevsk]
Generated description
Yegoryevsk is a historic town in Russia, now part of Moscow Oblast, known for its 19th-century architecture and industrial heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Yegoryevsk
Target entity description: Yegoryevsk is a historic town in Russia, now part of Moscow Oblast, known for its 19th-century architecture and industrial heritage.
  • A. Orekhovo
    Orekhovo is a Moscow Metro station on the Zamoskvoretskaya Line serving the Orekhovo-Borisovo district in southern Moscow.
  • B. Yuryev
    Yuryev is a historical name for the Estonian city now known as Tartu, reflecting its past under various regional powers.
  • C. Pleskov
    Pleskov is an alternative historical or variant name for the Russian city of Pskov, a historic regional center in northwestern Russia.
  • D. Petrovskoye
    Petrovskoye was the original Russian fortress settlement that later developed into the modern city of Makhachkala in Dagestan, Russia.
  • E. Yuzovka
    Yuzovka was the original name of the industrial settlement in eastern Ukraine that later developed into the city of Donetsk.
  • 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_69ca82abaffc8190ab8af79cdbc31ab3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3d722fbc8190b22745b581421f16 completed March 31, 2026, 3:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63c1f76881909ad6d7777090f2e2 completed April 1, 2026, 12:16 a.m.
NEDg Description generation batch_69cc651b4be08190ad76c70b1d617c1a completed April 1, 2026, 12:21 a.m.
NED2 Entity disambiguation (via description) batch_69cc664700dc819097d149931cf49673 completed April 1, 2026, 12:26 a.m.
Created at: March 30, 2026, 5:19 p.m.