Triple

T8871289
Position Surface form Disambiguated ID Type / Status
Subject Cherkessk E211161 entity
Predicate formerName P65 FINISHED
Object Sulimov
Sulimov was the former name of the city now known as Cherkessk, the capital of Karachay-Cherkessia in southwestern Russia.
 E763440 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: Sulimov | Statement: [Cherkessk, formerName, Sulimov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sulimov
Context triple: [Cherkessk, formerName, Sulimov]
  • A. Semyonov
    Semyonov is a common Russian surname borne by numerous notable figures in fields such as literature, science, and military history.
  • B. Rakhumov
    Rakhumov is a character from Fyodor Dostoevsky’s epistolary novel "Poor Folk," which explores the lives and struggles of impoverished residents in 19th-century St. Petersburg.
  • C. Yuryatin
    Yuryatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Lara Antipova’s story.
  • D. Khokhlov
    Khokhlov is a Russian surname commonly found in Eastern Europe, typically indicating Slavic heritage.
  • E. Kozlov
    Kozlov is a historic Russian town, now known as Michurinsk, that developed as a significant regional center of trade and agriculture.
  • 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: Sulimov
Triple: [Cherkessk, formerName, Sulimov]
Generated description
Sulimov was the former name of the city now known as Cherkessk, the capital of Karachay-Cherkessia in southwestern Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sulimov
Target entity description: Sulimov was the former name of the city now known as Cherkessk, the capital of Karachay-Cherkessia in southwestern Russia.
  • A. Semyonov
    Semyonov is a common Russian surname borne by numerous notable figures in fields such as literature, science, and military history.
  • B. Rakhumov
    Rakhumov is a character from Fyodor Dostoevsky’s epistolary novel "Poor Folk," which explores the lives and struggles of impoverished residents in 19th-century St. Petersburg.
  • C. Yuryatin
    Yuryatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Lara Antipova’s story.
  • D. Khokhlov
    Khokhlov is a Russian surname commonly found in Eastern Europe, typically indicating Slavic heritage.
  • E. Kozlov
    Kozlov is a historic Russian town, now known as Michurinsk, that developed as a significant regional center of trade and agriculture.
  • 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_69ca838d3c7c8190a849566d5afd2b11 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6126d2f88190979ab25772ee657c completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0ea9f5c8190b5c32fb1fefdc68b completed April 3, 2026, 11:13 a.m.
NEDg Description generation batch_69cfa191d7d0819085a6b9bf7fa56067 completed April 3, 2026, 11:16 a.m.
NED2 Entity disambiguation (via description) batch_69cfa28b1d1c8190ab4a10ba8fa7259d completed April 3, 2026, 11:20 a.m.
Created at: March 30, 2026, 6:51 p.m.