Triple

T1201755
Position Surface form Disambiguated ID Type / Status
Subject Krasnodar Krai E25796 entity
Predicate hasCity P316 FINISHED
Object Armavir
Armavir is a city in southwestern Russia known as an industrial and transportation center on the Kuban River.
 E194054 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: Armavir | Statement: [Krasnodar Krai, hasCity, Armavir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Armavir
Context triple: [Krasnodar Krai, hasCity, Armavir]
  • A. Gelendzhik
    Gelendzhik is a Black Sea resort city in southern Russia known for its beaches, scenic bay, and tourism infrastructure.
  • B. Stavropol
    Stavropol is a major administrative, cultural, and economic center in southwestern Russia, serving as the capital of Stavropol Krai in the North Caucasus region.
  • C. Nalchik
    Nalchik is the capital city of Russia’s Kabardino-Balkaria Republic in the North Caucasus, known for its diverse ethnic communities and role as a regional cultural and administrative center.
  • D. Astapovo
    Astapovo is a small Russian railway station village historically known as the place where the writer Leo Tolstoy died in 1910.
  • E. Gatchina
    Gatchina is a historic Russian town near Saint Petersburg, known for its imperial palace complex and long association with the Romanov dynasty.
  • 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: Armavir
Triple: [Krasnodar Krai, hasCity, Armavir]
Generated description
Armavir is a city in southwestern Russia known as an industrial and transportation center on the Kuban River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Armavir
Target entity description: Armavir is a city in southwestern Russia known as an industrial and transportation center on the Kuban River.
  • A. Gelendzhik
    Gelendzhik is a Black Sea resort city in southern Russia known for its beaches, scenic bay, and tourism infrastructure.
  • B. Stavropol
    Stavropol is a major administrative, cultural, and economic center in southwestern Russia, serving as the capital of Stavropol Krai in the North Caucasus region.
  • C. Nalchik
    Nalchik is the capital city of Russia’s Kabardino-Balkaria Republic in the North Caucasus, known for its diverse ethnic communities and role as a regional cultural and administrative center.
  • D. Astapovo
    Astapovo is a small Russian railway station village historically known as the place where the writer Leo Tolstoy died in 1910.
  • E. Gatchina
    Gatchina is a historic Russian town near Saint Petersburg, known for its imperial palace complex and long association with the Romanov dynasty.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd9fece4819089a6a2d61e61fa2e completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad8a9f91808190b44715dc3df31cc3 completed March 8, 2026, 2:41 p.m.
NEDg Description generation batch_69ad95738df081909e56178cc1e0ab74 completed March 8, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69ad97a1a44c8190a9d8fe05837ec9ff completed March 8, 2026, 3:37 p.m.
Created at: March 1, 2026, 7:46 p.m.