Triple

T13254047
Position Surface form Disambiguated ID Type / Status
Subject Sumy E315609 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object BM
BM is the vehicle registration code assigned to the city of Sumy in Ukraine.
 E1031114 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: BM | Statement: [Sumy, hasVehicleRegistrationCode, BM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BM
Context triple: [Sumy, hasVehicleRegistrationCode, BM]
  • A. BM
    BM is the regional vehicle registration code used on license plates for motor vehicles registered in Pekanbaru, Indonesia.
  • B. BM
    BM is the post-nominal abbreviation used to denote recipients of the Bravery Medal, an Australian award for acts of courage.
  • C. BM
    BM is the abbreviated name of Hungary’s Ministry of the Interior, the government body responsible for internal affairs, law enforcement, and public administration.
  • D. BM
    BM is the vehicle registration code used on license plates for vehicles registered in the Cologne Government Region of Germany.
  • E. BMN
    BMN is the National Rail station code for Bromley North railway station in the London Borough of Bromley, England.
  • 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: BM
Triple: [Sumy, hasVehicleRegistrationCode, BM]
Generated description
BM is the vehicle registration code assigned to the city of Sumy in Ukraine.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BM
Target entity description: BM is the vehicle registration code assigned to the city of Sumy in Ukraine.
  • A. BM
    BM is the regional vehicle registration code used on license plates for motor vehicles registered in Pekanbaru, Indonesia.
  • B. BM
    BM is the post-nominal abbreviation used to denote recipients of the Bravery Medal, an Australian award for acts of courage.
  • C. BM
    BM is the abbreviated name of Hungary’s Ministry of the Interior, the government body responsible for internal affairs, law enforcement, and public administration.
  • D. BM
    BM is the vehicle registration code used on license plates for vehicles registered in the Cologne Government Region of Germany.
  • E. BMN
    BMN is the National Rail station code for Bromley North railway station in the London Borough of Bromley, England.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98f7517048190b4eac4e44e81ff66 completed April 11, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a3d6b808190b4ae5225961de03f completed May 3, 2026, 8:41 a.m.
NEDg Description generation batch_69f70bc5111c8190ae5b098c806bb845 completed May 3, 2026, 8:48 a.m.
NED2 Entity disambiguation (via description) batch_69f70ca343f08190b6484f464ed40810 completed May 3, 2026, 8:51 a.m.
Created at: April 9, 2026, 9:24 p.m.