Triple

T14818223
Position Surface form Disambiguated ID Type / Status
Subject Kragujevac E348374 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object KG
KG is the vehicle registration code used on license plates for the Serbian city of Kragujevac.
E1121509 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: KG | Statement: [Kragujevac, vehicleRegistrationCode, KG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KG
Context triple: [Kragujevac, vehicleRegistrationCode, KG]
  • A. KG
    KG is the post-nominal abbreviation used by Knights of the Order of the Garter, the highest order of chivalry in the United Kingdom.
  • B. KG
    KG is the widely used nickname of Kevin Garnett, a Hall of Fame NBA forward known for his intensity, defensive prowess, and versatility.
  • C. KG
    KG is the vehicle registration code used on license plates for the Bad Kissingen district in Bavaria, Germany.
  • D. KGKT
    KGKT is the ICAO airport code for Gatlinburg–Pigeon Forge Airport, a public airport serving the Gatlinburg and Pigeon Forge area in Tennessee, USA.
  • E. KGX
    KGX is the National Rail station code for London King's Cross, a major central London railway terminus and transport hub.
  • 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: KG
Triple: [Kragujevac, vehicleRegistrationCode, KG]
Generated description
KG is the vehicle registration code used on license plates for the Serbian city of Kragujevac.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: KG
Target entity description: KG is the vehicle registration code used on license plates for the Serbian city of Kragujevac.
  • A. KG
    KG is the post-nominal abbreviation used by Knights of the Order of the Garter, the highest order of chivalry in the United Kingdom.
  • B. KG
    KG is the widely used nickname of Kevin Garnett, a Hall of Fame NBA forward known for his intensity, defensive prowess, and versatility.
  • C. KG
    KG is the vehicle registration code used on license plates for the Bad Kissingen district in Bavaria, Germany.
  • D. KGKT
    KGKT is the ICAO airport code for Gatlinburg–Pigeon Forge Airport, a public airport serving the Gatlinburg and Pigeon Forge area in Tennessee, USA.
  • E. KGX
    KGX is the National Rail station code for London King's Cross, a major central London railway terminus and transport hub.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe4cf38819090f25ef045351d5d completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe389940e081908ad627955cb8d52e completed May 8, 2026, 7:25 p.m.
NEDg Description generation batch_69fe3a315d2c81908db44e7792908e39 completed May 8, 2026, 7:32 p.m.
NED2 Entity disambiguation (via description) batch_69fe3bda81cc8190b256ec6284383dde completed May 8, 2026, 7:39 p.m.
Created at: April 10, 2026, 1:50 a.m.