Triple

T21116363
Position Surface form Disambiguated ID Type / Status
Subject BMP-1 E520308 entity
Predicate engineModel P2092 FINISHED
Object UTD-20
The UTD-20 is a Soviet-designed V-6 diesel engine widely used to power BMP-series infantry fighting vehicles and other armored platforms.
 E1467669 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: UTD-20 | Statement: [BMP-1, engineModel, UTD-20]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UTD-20
Context triple: [BMP-1, engineModel, UTD-20]
  • A. TUDa
    TUDa is a leading German research university located in Darmstadt, renowned for its engineering, computer science, and natural sciences programs.
  • B. UDT
    UDT (Timorese Democratic Union) is a political party in East Timor that played a key role in the country’s independence struggle and later became part of the National Council of Timorese Resistance.
  • C. UTY
    UTY is the ICAO airline designator assigned to Alliance Airlines, an Australian regional and charter carrier.
  • D. UTN
    UTN is the IATA airport code for Upington Airport, a regional airport serving the town of Upington in South Africa.
  • E. UTU
    UTU is the commonly used abbreviation for the University of Turku, a major multidisciplinary university in Turku, Finland.
  • 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: UTD-20
Triple: [BMP-1, engineModel, UTD-20]
Generated description
The UTD-20 is a Soviet-designed V-6 diesel engine widely used to power BMP-series infantry fighting vehicles and other armored platforms.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UTD-20
Target entity description: The UTD-20 is a Soviet-designed V-6 diesel engine widely used to power BMP-series infantry fighting vehicles and other armored platforms.
  • A. TUDa
    TUDa is a leading German research university located in Darmstadt, renowned for its engineering, computer science, and natural sciences programs.
  • B. UDT
    UDT (Timorese Democratic Union) is a political party in East Timor that played a key role in the country’s independence struggle and later became part of the National Council of Timorese Resistance.
  • C. UTY
    UTY is the ICAO airline designator assigned to Alliance Airlines, an Australian regional and charter carrier.
  • D. UTN
    UTN is the IATA airport code for Upington Airport, a regional airport serving the town of Upington in South Africa.
  • E. UTU
    UTU is the commonly used abbreviation for the University of Turku, a major multidisciplinary university in Turku, Finland.
  • 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_69e0b509a318819092fbbcb21d1fe603 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e72106a3b48190a0efa51a74ae21f0 completed April 21, 2026, 7:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0965e3e1888190b953dbd7209a3c4c completed May 17, 2026, 6:53 a.m.
NEDg Description generation batch_6a09669ac9988190ba5ec8bcf8dc7eb4 completed May 17, 2026, 6:56 a.m.
NED2 Entity disambiguation (via description) batch_6a0967821ce08190a23d22439c343f49 completed May 17, 2026, 7 a.m.
Created at: April 16, 2026, 2:55 p.m.