Triple

T9857940
Position Surface form Disambiguated ID Type / Status
Subject People's Commissariat of the Navy of the USSR E239634 entity
Predicate shortName P43 FINISHED
Object NKVMF
NKVMF was the abbreviated name of the People's Commissariat responsible for overseeing the Soviet Union's naval forces before and during World War II.
 E825725 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: NKVMF | Statement: [People's Commissariat of the Navy of the USSR, shortName, NKVMF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NKVMF
Context triple: [People's Commissariat of the Navy of the USSR, shortName, NKVMF]
  • A. Knv
    Knv is the station code for Knivsta railway station in Sweden.
  • B. NKo
    NKo is a Unicode block that encodes the characters of the N’Ko script used for writing several West African Mande languages.
  • C. NK
    NK is the two-letter IATA airline designator assigned to Spirit Airlines, a U.S.-based ultra-low-cost carrier.
  • D. NK
    NK is the station code for Nashik Road railway station, a major rail hub serving the city of Nashik in Maharashtra, India.
  • E. NK
    NK is the vehicle registration code used on license plates for the Neunkirchen district in Germany.
  • 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: NKVMF
Triple: [People's Commissariat of the Navy of the USSR, shortName, NKVMF]
Generated description
NKVMF was the abbreviated name of the People's Commissariat responsible for overseeing the Soviet Union's naval forces before and during World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NKVMF
Target entity description: NKVMF was the abbreviated name of the People's Commissariat responsible for overseeing the Soviet Union's naval forces before and during World War II.
  • A. Knv
    Knv is the station code for Knivsta railway station in Sweden.
  • B. NKo
    NKo is a Unicode block that encodes the characters of the N’Ko script used for writing several West African Mande languages.
  • C. NK
    NK is the two-letter IATA airline designator assigned to Spirit Airlines, a U.S.-based ultra-low-cost carrier.
  • D. NK
    NK is the station code for Nashik Road railway station, a major rail hub serving the city of Nashik in Maharashtra, India.
  • E. NK
    NK is the vehicle registration code used on license plates for the Neunkirchen district in Germany.
  • 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_69ca84e6493081909cf58c8d42ea856b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb399bd8081908281d1735cc3909f completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e43b2de881909e00f6701d1c7b54 completed April 5, 2026, 4:25 a.m.
NEDg Description generation batch_69d1e5204f748190b1f56ee5469828a2 completed April 5, 2026, 4:29 a.m.
NED2 Entity disambiguation (via description) batch_69d1e598243481909278cb3c911ce3db completed April 5, 2026, 4:31 a.m.
Created at: March 30, 2026, 8:35 p.m.