Triple

T687390
Position Surface form Disambiguated ID Type / Status
Subject Moscow Oblast E13313 entity
Predicate contains P35 FINISHED
Object Serpukhov
Serpukhov is a historic Russian town south of Moscow known for its medieval monasteries, industrial heritage, and location on the Nara River.
 E129360 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: Serpukhov | Statement: [Moscow Oblast, contains, Serpukhov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Serpukhov
Context triple: [Moscow Oblast, contains, Serpukhov]
  • A. Lyubertsy
    Lyubertsy is a city in Russia that serves as a major suburban and industrial center just southeast of Moscow.
  • B. 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.
  • C. Noginsk
    Noginsk is a town in western Russia that serves as an industrial and transport center east of Moscow.
  • D. Elektrostal
    Elektrostal is an industrial city in Russia known for its metallurgical and engineering industries, located east of Moscow.
  • E. Podolsk
    Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
  • 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: Serpukhov
Triple: [Moscow Oblast, contains, Serpukhov]
Generated description
Serpukhov is a historic Russian town south of Moscow known for its medieval monasteries, industrial heritage, and location on the Nara River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Serpukhov
Target entity description: Serpukhov is a historic Russian town south of Moscow known for its medieval monasteries, industrial heritage, and location on the Nara River.
  • A. Lyubertsy
    Lyubertsy is a city in Russia that serves as a major suburban and industrial center just southeast of Moscow.
  • B. 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.
  • C. Noginsk
    Noginsk is a town in western Russia that serves as an industrial and transport center east of Moscow.
  • D. Elektrostal
    Elektrostal is an industrial city in Russia known for its metallurgical and engineering industries, located east of Moscow.
  • E. Podolsk
    Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
  • 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_69ac598bddf88190afc565deec2357a1 completed March 7, 2026, 4:59 p.m.
NEDg Description generation batch_69ac5a8106f881908889e779b43931b9 completed March 7, 2026, 5:04 p.m.
NED2 Entity disambiguation (via description) batch_69ac5ae66abc81909f1d9a563e9e7248 completed March 7, 2026, 5:05 p.m.
Created at: March 1, 2026, 7:36 p.m.