Triple

T20395557
Position Surface form Disambiguated ID Type / Status
Subject Schwaz E500192 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object SZ
SZ is the vehicle registration code used for the Austrian district of Schwaz in the state of Tyrol.
 E1428505 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: [Schwaz, vehicleRegistrationCode, SZ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SZ
Context triple: [Schwaz, vehicleRegistrationCode, SZ]
  • A. SZ
    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. SZ
    SZ is the official abbreviation for the Swiss canton of Schwyz, one of the founding cantons of Switzerland.
  • D. 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.
  • E. SZF
    SZF is the IATA airport code for Samsun-Çarşamba Airport, a regional airport serving the city of Samsun in northern Turkey.
  • 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: [Schwaz, vehicleRegistrationCode, SZ]
Generated description
SZ is the vehicle registration code used for the Austrian district of Schwaz in the state of Tyrol.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SZ
Target entity description: SZ is the vehicle registration code used for the Austrian district of Schwaz in the state of Tyrol.
  • A. SZ
    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. SZ
    SZ is the official abbreviation for the Swiss canton of Schwyz, one of the founding cantons of Switzerland.
  • D. 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.
  • E. SZF
    SZF is the commonly used abbreviation for the Faculty of Social Sciences at the University of Latvia, encompassing disciplines such as sociology, communication, and political science.
  • 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_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67912d7948190ac2fda8ce95e5c70 completed April 20, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08762804ac81909e90e7983246cb28 completed May 16, 2026, 1:50 p.m.
NEDg Description generation batch_6a0877d6b364819080b5e701acea02aa completed May 16, 2026, 1:57 p.m.
NED2 Entity disambiguation (via description) batch_6a08787cfe6c8190881554ead3cfd248 completed May 16, 2026, 2 p.m.
Created at: April 16, 2026, 11:28 a.m.