Triple

T18313404
Position Surface form Disambiguated ID Type / Status
Subject Karlovac E438687 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object KA
KA is the vehicle registration code used on license plates for the city of Karlovac in Croatia.
E1318516 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: KA | Statement: [Karlovac, vehicleRegistrationCode, KA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KA
Context triple: [Karlovac, vehicleRegistrationCode, KA]
  • A. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • B. KA
    KA is a postcode area in the United Kingdom covering parts of southwest Scotland, including towns such as Kilmarnock and Irvine.
  • C. KA
    KA is the IATA airline designator for Cathay Dragon, a former Hong Kong-based regional carrier owned by Cathay Pacific.
  • D. KA
    KA is the vehicle registration code for the Indian state of Karnataka.
  • E. Ka
    Ka is an American underground rapper and producer from Brownsville, Brooklyn, known for his minimalist, introspective style and dense, poetic lyricism.
  • 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: KA
Triple: [Karlovac, vehicleRegistrationCode, KA]
Generated description
KA is the vehicle registration code used on license plates for the city of Karlovac in Croatia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: KA
Target entity description: KA is the vehicle registration code used on license plates for the city of Karlovac in Croatia.
  • A. KA
    KA is the vehicle registration code used on license plates for cars registered in the German city of Karlsruhe.
  • B. KA
    KA is a postcode area in the United Kingdom covering parts of southwest Scotland, including towns such as Kilmarnock and Irvine.
  • C. KA
    KA is the IATA airline designator for Cathay Dragon, a former Hong Kong-based regional carrier owned by Cathay Pacific.
  • D. KA
    KA is the vehicle registration code for the Indian state of Karnataka.
  • E. Ka
    Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
  • 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_69d8b916a2d081909e249e4902f6aad9 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5021b7e2c81908cd3b6684ab899f6 completed April 19, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03c4c1d8048190916dcc7146d15bc4 completed May 13, 2026, 12:24 a.m.
NEDg Description generation batch_6a03c66b72a0819081fe77b42060d6de completed May 13, 2026, 12:31 a.m.
NED2 Entity disambiguation (via description) batch_6a03c6f191b081909a0e65fa1d553b82 completed May 13, 2026, 12:33 a.m.
Created at: April 10, 2026, 10:36 a.m.