Triple

T7565663
Position Surface form Disambiguated ID Type / Status
Subject Lazarevsky District E178905 entity
Predicate hasSettlement P1068 FINISHED
Object Sovet-Kvadzhe
Sovet-Kvadzhe is a rural settlement located within the Lazarevsky District of Krasnodar Krai, Russia, near the Black Sea coast.
E672713 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: Sovet-Kvadzhe | Statement: [Lazarevsky District, hasSettlement, Sovet-Kvadzhe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sovet-Kvadzhe
Context triple: [Lazarevsky District, hasSettlement, Sovet-Kvadzhe]
  • A. Georgievsk
    Georgievsk is a town in Russia’s Stavropol Krai, historically notable as the site where the 1783 Treaty of Georgievsk between the Russian Empire and the Kingdom of Kartli-Kakheti was signed.
  • B. Tselinograd
    Tselinograd was the Soviet-era name of Kazakhstan’s capital city, now known as Astana.
  • C. Samokov
    Samokov is a Bulgarian town in the Rila Mountains known historically for its ironworking and as a gateway to nearby ski and hiking areas.
  • D. Maloyaroslavets
    Maloyaroslavets is a historic town in western Russia known for the 1812 Battle of Maloyaroslavets during Napoleon’s invasion.
  • E. Kızılay
    Kızılay is a central district and major commercial hub in Ankara, Turkey, known for its busy squares, offices, shops, and public transportation connections.
  • 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: Sovet-Kvadzhe
Triple: [Lazarevsky District, hasSettlement, Sovet-Kvadzhe]
Generated description
Sovet-Kvadzhe is a rural settlement located within the Lazarevsky District of Krasnodar Krai, Russia, near the Black Sea coast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sovet-Kvadzhe
Target entity description: Sovet-Kvadzhe is a rural settlement located within the Lazarevsky District of Krasnodar Krai, Russia, near the Black Sea coast.
  • A. Georgievsk
    Georgievsk is a town in Russia’s Stavropol Krai, historically notable as the site where the 1783 Treaty of Georgievsk between the Russian Empire and the Kingdom of Kartli-Kakheti was signed.
  • B. Tselinograd
    Tselinograd was the Soviet-era name of Kazakhstan’s capital city, now known as Astana.
  • C. Samokov
    Samokov is a Bulgarian town in the Rila Mountains known historically for its ironworking and as a gateway to nearby ski and hiking areas.
  • D. Maloyaroslavets
    Maloyaroslavets is a historic town in western Russia known for the 1812 Battle of Maloyaroslavets during Napoleon’s invasion.
  • E. Kızılay
    Kızılay is a central district and major commercial hub in Ankara, Turkey, known for its busy squares, offices, shops, and public transportation connections.
  • 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_69c69f2f80288190b95cceb4da92ab2b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8fde87c81909795fc713d7378ff completed March 27, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856dc5ea881908c2e0075f9631af4 completed March 28, 2026, 10:31 p.m.
NEDg Description generation batch_69c8575116c481909aa2bebb997e2883 completed March 28, 2026, 10:33 p.m.
NED2 Entity disambiguation (via description) batch_69c857d522dc8190ae3c4734ac428334 completed March 28, 2026, 10:36 p.m.
Created at: March 27, 2026, 3:50 p.m.