Triple

T16887081
Position Surface form Disambiguated ID Type / Status
Subject Szombathely E421565 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object SZ
SZ is the vehicle registration code used on license plates for vehicles registered in the Hungarian city of Szombathely.
 E367050 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: SZ | Statement: [Szombathely, vehicleRegistrationCode, SZ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SZ
Context triple: [Szombathely, vehicleRegistrationCode, SZ]
  • A. SZ
    SZ is the official station code used to identify the Berlin U-Bahn station Seestraße.
  • B. SZ
    SZ is the vehicle registration code for the German city of Salzgitter in Lower Saxony.
  • C. S/Z
    S/Z is Roland Barthes’s influential structuralist analysis of Balzac’s short story “Sarrasine,” renowned for its detailed demonstration of textual codes and readerly versus writerly texts.
  • D. SZF
    SZF is the IATA airport code for Samsun-Çarşamba Airport, a regional airport serving the city of Samsun in northern Turkey.
  • E. SZB
    SZB is a German vehicle registration code assigned to the Erzgebirgskreis district in the state of Saxony.
  • 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: SZ
Triple: [Szombathely, vehicleRegistrationCode, SZ]
Generated description
SZ is the vehicle registration code used on license plates for vehicles registered in the Hungarian city of Szombathely.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SZ
Target entity description: SZ is the vehicle registration code used on license plates for vehicles registered in the Hungarian city of Szombathely.
  • A. SZ chosen
    SZ is the vehicle registration code for the German city of Salzgitter in Lower Saxony.
  • B. SZ
    SZ is the official station code used to identify the Berlin U-Bahn station Seestraße.
  • C. S/Z
    S/Z is Roland Barthes’s influential structuralist analysis of Balzac’s short story “Sarrasine,” renowned for its detailed demonstration of textual codes and readerly versus writerly texts.
  • D. SZF
    SZF is the IATA airport code for Samsun-Çarşamba Airport, a regional airport serving the city of Samsun in northern Turkey.
  • E. SZB
    SZB is a German vehicle registration code assigned to the Erzgebirgskreis district in the state of Saxony.
  • F. None of above.

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_69d889d470fc8190b4aec199636c0c56 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc1f42481909dcf595358c23497 completed April 18, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c2befaa88190ba83dc17aa66b541 completed May 10, 2026, 5:39 p.m.
NEDg Description generation batch_6a00c392b4488190bcfcb40351821f92 completed May 10, 2026, 5:42 p.m.
NED2 Entity disambiguation (via description) batch_6a00c44e37b48190a62b315ddbbd4ec4 completed May 10, 2026, 5:45 p.m.
Created at: April 10, 2026, 5:29 a.m.