Triple

T6019370
Position Surface form Disambiguated ID Type / Status
Subject Oslo county E134025 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object OS
OS is the vehicle registration code used on license plates for vehicles registered in Oslo, Norway.
E562151 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: OS | Statement: [Oslo county, hasVehicleRegistrationCode, OS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OS
Context triple: [Oslo county, hasVehicleRegistrationCode, OS]
  • A. OS
    OS is the two-letter IATA airline designator assigned to Austrian Airlines, the flag carrier of Austria.
  • B. OS
    OS is the vehicle registration code for the German city of Osnabrück and its surrounding district.
  • C. OSE
    OSE is the abbreviation for the Osaka Securities Exchange, a major Japanese stock exchange based in Osaka.
  • D. OS SR
    OS SR is the official abbreviation for the Slovak Armed Forces, the military organization responsible for the defense of Slovakia.
  • E. OS/2
    OS/2 is a 32-bit multitasking operating system originally developed by IBM and Microsoft as a successor to MS-DOS, known for its stability and use in business environments in the late 1980s and 1990s.
  • 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: OS
Triple: [Oslo county, hasVehicleRegistrationCode, OS]
Generated description
OS is the vehicle registration code used on license plates for vehicles registered in Oslo, Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: OS
Target entity description: OS is the vehicle registration code used on license plates for vehicles registered in Oslo, Norway.
  • A. OS
    OS is the vehicle registration code for the German city of Osnabrück and its surrounding district.
  • B. OS
    OS is the two-letter IATA airline designator assigned to Austrian Airlines, the flag carrier of Austria.
  • C. OSE
    OSE is the abbreviation for the Osaka Securities Exchange, a major Japanese stock exchange based in Osaka.
  • D. OS SR
    OS SR is the official abbreviation for the Slovak Armed Forces, the military organization responsible for the defense of Slovakia.
  • E. OS/2
    OS/2 is a 32-bit multitasking operating system originally developed by IBM and Microsoft as a successor to MS-DOS, known for its stability and use in business environments in the late 1980s and 1990s.
  • 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_69c008742a5c8190b9cb9c2787a3d8b3 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04f86efec8190bc357dddf6ebb4a9 completed March 22, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c108be2170819084b4b940e52b0185 completed March 23, 2026, 9:32 a.m.
NEDg Description generation batch_69c10abc9aa08190acf1ced6a8be322e completed March 23, 2026, 9:41 a.m.
NED2 Entity disambiguation (via description) batch_69c10b5c118c8190aaf5461c40472022 completed March 23, 2026, 9:43 a.m.
Created at: March 22, 2026, 4:07 p.m.