Triple

T4970164
Position Surface form Disambiguated ID Type / Status
Subject Kaluga Oblast E111628 entity
Predicate containsCity P294 FINISHED
Object Spas-Demensk
Spas-Demensk is a small town in western Russia known for its historical role in World War II and its location within Kaluga Oblast.
 E482705 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: Spas-Demensk | Statement: [Kaluga Oblast, containsCity, Spas-Demensk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Spas-Demensk
Context triple: [Kaluga Oblast, containsCity, Spas-Demensk]
  • A. Maryina Roshcha
    Maryina Roshcha is a Moscow Metro station on the Big Circle Line serving the Maryina Roshcha district in Russia’s capital.
  • B. Kuchlak
    Kuchlak is a town in Balochistan, Pakistan, situated near Quetta and known as a local commercial and transit hub in the region.
  • C. Zyuzino
    Zyuzino is a Moscow Metro station on the Big Circle Line serving the Zyuzino District in southern Moscow.
  • D. Krasnov
    Krasnov is a Russian surname borne by various notable figures in military, political, and cultural history.
  • E. Oreshek
    Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
  • 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: Spas-Demensk
Triple: [Kaluga Oblast, containsCity, Spas-Demensk]
Generated description
Spas-Demensk is a small town in western Russia known for its historical role in World War II and its location within Kaluga Oblast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Spas-Demensk
Target entity description: Spas-Demensk is a small town in western Russia known for its historical role in World War II and its location within Kaluga Oblast.
  • A. Maryina Roshcha
    Maryina Roshcha is a Moscow Metro station on the Big Circle Line serving the Maryina Roshcha district in Russia’s capital.
  • B. Kuchlak
    Kuchlak is a town in Balochistan, Pakistan, situated near Quetta and known as a local commercial and transit hub in the region.
  • C. Zyuzino
    Zyuzino is a Moscow Metro station on the Big Circle Line serving the Zyuzino District in southern Moscow.
  • D. Krasnov
    Krasnov is a Russian surname borne by various notable figures in military, political, and cultural history.
  • E. Oreshek
    Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
  • 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_69bd441a0eb481908050fa4273b19eae completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd721221b88190916feb9b4f049195 completed March 20, 2026, 4:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81f749fc8190ad4dc68f7e2086b1 completed March 21, 2026, 11:33 a.m.
NEDg Description generation batch_69be841943d481909c18ca8e8c758501 completed March 21, 2026, 11:42 a.m.
NED2 Entity disambiguation (via description) batch_69be848b0df88190aba28a258d8a706e completed March 21, 2026, 11:44 a.m.
Created at: March 20, 2026, 1:33 p.m.