Triple

T17205459
Position Surface form Disambiguated ID Type / Status
Subject Šakiai E417588 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object SK
SK is the vehicle registration code used for motor vehicles registered in the town of Šakiai in Lithuania.
 E1256785 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: SK | Statement: [Šakiai, vehicleRegistrationCode, SK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SK
Context triple: [Šakiai, vehicleRegistrationCode, SK]
  • A. SK
    SK is the postcode area covering Stockport and surrounding parts of Greater Manchester and nearby counties in North West England.
  • B. SK
    SK is the official vehicle registration code assigned to the Indian state of Sikkim.
  • C. SK
    SK is the IATA airline designator used worldwide to identify Scandinavian Airlines on tickets, timetables, and flight information systems.
  • D. SK
    SK is the ISO 3166-1 alpha-2 country code for Slovakia, a landlocked Central European nation known for its mountains, castles, and membership in the European Union.
  • E. SK
    SK is the vehicle registration code used on license plates for vehicles registered in Skopje, the capital city of North Macedonia.
  • 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: SK
Triple: [Šakiai, vehicleRegistrationCode, SK]
Generated description
SK is the vehicle registration code used for motor vehicles registered in the town of Šakiai in Lithuania.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SK
Target entity description: SK is the vehicle registration code used for motor vehicles registered in the town of Šakiai in Lithuania.
  • A. SK
    SK is the vehicle registration code for the district of Saalekreis in the German state of Saxony-Anhalt.
  • B. SK
    SK is the vehicle registration code used on license plates for vehicles registered in Skopje, the capital city of North Macedonia.
  • C. SK
    SK is the official vehicle registration code assigned to the Indian state of Sikkim.
  • D. SK
    SK is the ISO 3166-1 alpha-2 country code for Slovakia, a landlocked Central European nation known for its mountains, castles, and membership in the European Union.
  • E. SK
    SK is the IATA airline designator used worldwide to identify Scandinavian Airlines on tickets, timetables, and flight information systems.
  • 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_69d886d6ba8c819093215917b3d01689 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42dc0bea8819090946615a14b2d86 completed April 19, 2026, 1:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a015fde8ba08190ae88dc9ea3366a68 completed May 11, 2026, 4:49 a.m.
NEDg Description generation batch_6a0161b31540819098aa6275f96433ad completed May 11, 2026, 4:57 a.m.
NED2 Entity disambiguation (via description) batch_6a016299d9ac8190be74d5db0d28ea36 completed May 11, 2026, 5:01 a.m.
Created at: April 10, 2026, 5:38 a.m.