Triple

T2469058
Position Surface form Disambiguated ID Type / Status
Subject Kiev Special Military District E55324 entity
Predicate abbreviation P43 FINISHED
Object KOVO
KOVO was the Russian abbreviation for the Kiev Special Military District, a major pre–World War II military-administrative region of the Soviet Union centered around Kiev.
 E269630 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: KOVO | Statement: [Kiev Special Military District, abbreviation, KOVO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KOVO
Context triple: [Kiev Special Military District, abbreviation, KOVO]
  • A. Kokota
    Kokota is an Oceanic language spoken in the Solomon Islands, particularly on Santa Isabel Island.
  • B. Karlov
    Karlov is a historic university campus complex in Prague that houses several faculties of Charles University, particularly in the medical and natural sciences.
  • C. Čukarica
    Čukarica is a municipality of Belgrade known for its mix of urban neighborhoods, industrial zones, and green areas along the Sava River.
  • D. Krk
    Krk is a large Adriatic Sea island in the northern part of Croatia, known for its historic towns, beaches, and popular tourist resorts.
  • E. Cocijo
    Cocijo is the Zapotec rain and storm deity, associated with fertility, lightning, and agricultural abundance in Mesoamerican religion.
  • 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: KOVO
Triple: [Kiev Special Military District, abbreviation, KOVO]
Generated description
KOVO was the Russian abbreviation for the Kiev Special Military District, a major pre–World War II military-administrative region of the Soviet Union centered around Kiev.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KOVO
Target entity description: KOVO was the Russian abbreviation for the Kiev Special Military District, a major pre–World War II military-administrative region of the Soviet Union centered around Kiev.
  • A. Kokota
    Kokota is an Oceanic language spoken in the Solomon Islands, particularly on Santa Isabel Island.
  • B. Karlov
    Karlov is a historic university campus complex in Prague that houses several faculties of Charles University, particularly in the medical and natural sciences.
  • C. Čukarica
    Čukarica is a municipality of Belgrade known for its mix of urban neighborhoods, industrial zones, and green areas along the Sava River.
  • D. Krk
    Krk is a large Adriatic Sea island in the northern part of Croatia, known for its historic towns, beaches, and popular tourist resorts.
  • E. Cocijo
    Cocijo is the Zapotec rain and storm deity, associated with fertility, lightning, and agricultural abundance in Mesoamerican religion.
  • 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_69ab49e3622c8190ad22afa2c4fbb807 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd134684c8190bc62c0af22d75538 completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17a29c2c8190b9e7b49d086ad9d5 completed March 9, 2026, 6:55 p.m.
NEDg Description generation batch_69af183b63848190ac62869b1fdb672c completed March 9, 2026, 6:58 p.m.
NED2 Entity disambiguation (via description) batch_69af18fc1a0c8190aeb24f304cbba35b completed March 9, 2026, 7:01 p.m.
Created at: March 6, 2026, 9:44 p.m.