Triple

T687376
Position Surface form Disambiguated ID Type / Status
Subject Moscow Oblast E13313 entity
Predicate contains P35 FINISHED
Object Podolsk
Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
E115415 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: Podolsk | Statement: [Moscow Oblast, contains, Podolsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Podolsk
Context triple: [Moscow Oblast, contains, Podolsk]
  • A. Dmitrov
    Dmitrov is a historic town in Moscow Oblast, Russia, located north of Moscow and known for its medieval kremlin and role as a regional cultural center.
  • B. Astapovo
    Astapovo is a small Russian railway station village historically known as the place where the writer Leo Tolstoy died in 1910.
  • C. Novo-Ogaryovo
    Novo-Ogaryovo is a suburban governmental estate outside Moscow that serves as one of the primary official residences of Russian President Vladimir Putin.
  • D. Yaroslavl
    Yaroslavl is a historic city in central Russia, located on the Volga River and known as one of the Golden Ring cities famed for its well-preserved medieval architecture and cultural heritage.
  • E. Krasnogorsk
    Krasnogorsk is a city in western Russia that serves as an important administrative and residential center just outside Moscow.
  • 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: Podolsk
Triple: [Moscow Oblast, contains, Podolsk]
Generated description
Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Podolsk
Target entity description: Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
  • A. Dmitrov
    Dmitrov is a historic town in Moscow Oblast, Russia, located north of Moscow and known for its medieval kremlin and role as a regional cultural center.
  • B. Astapovo
    Astapovo is a small Russian railway station village historically known as the place where the writer Leo Tolstoy died in 1910.
  • C. Novo-Ogaryovo
    Novo-Ogaryovo is a suburban governmental estate outside Moscow that serves as one of the primary official residences of Russian President Vladimir Putin.
  • D. Yaroslavl
    Yaroslavl is a historic city in central Russia, located on the Volga River and known as one of the Golden Ring cities famed for its well-preserved medieval architecture and cultural heritage.
  • E. Krasnogorsk
    Krasnogorsk is a city in western Russia that serves as an important administrative and residential center just outside Moscow.
  • 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_69a4933e0f98819097d22766c49b61b8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a0953fb481909e1d4177ee191351 completed March 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac1ccab5bc819099c0f060147c8f27 completed March 7, 2026, 12:40 p.m.
NEDg Description generation batch_69ac1d5960408190bf7dd3b8b64709db completed March 7, 2026, 12:43 p.m.
NED2 Entity disambiguation (via description) batch_69ac1dc56f7481909eb1ffb6b24db39f completed March 7, 2026, 12:44 p.m.
Created at: March 1, 2026, 7:36 p.m.