Triple

T11831362
Position Surface form Disambiguated ID Type / Status
Subject Komárno E281398 entity
Predicate usesVehicleRegistrationCode P1173 FINISHED
Object KN E941835 NE FINISHED

How this triple was built (2 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: KN | Statement: [Komárno, usesVehicleRegistrationCode, KN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KN
Context triple: [Komárno, usesVehicleRegistrationCode, KN]
  • A. KN
    KN is the IATA airline designator assigned to China United Airlines, a Chinese domestic carrier based in Beijing.
  • B. KN chosen
    KN is the vehicle registration code used for cars registered in the town of Kolárovo in Slovakia.
  • C. KEN
    KEN is the official FIFA trigramme used to represent the Kenya national football team in international competitions and records.
  • D. NK
    NK is the station code for Nashik Road railway station, a major rail hub serving the city of Nashik in Maharashtra, India.
  • E. NK
    NK is the vehicle registration code used on license plates for the Neunkirchen district in Germany.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6ab276f8c8190b1966a0ef11349ac completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a62c95988190a45dbaa7001c8846 completed April 10, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69f16741d9a08190b6d6d5e59dfa41b8 completed April 29, 2026, 2:04 a.m.
Created at: April 8, 2026, 9:43 p.m.