Triple

T18908315
Position Surface form Disambiguated ID Type / Status
Subject Správa železnic E462526 entity
Predicate abbreviation P43 FINISHED
Object SŽ
SŽ is the Czech national railway infrastructure manager responsible for operating, maintaining, and developing the country’s railway network.
 E1348432 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: SŽ | Statement: [Správa železnic, abbreviation, SŽ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SŽ
Context triple: [Správa železnic, abbreviation, SŽ]
  • A. 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.
  • B. SZĽH
    SZĽH is the Slovak Ice Hockey Federation, the governing body responsible for organizing and overseeing ice hockey activities and national teams in Slovakia.
  • C. SZ
    SZ is the official station code used to identify the Berlin U-Bahn station Seestraße.
  • D. SZ
    SZ is the vehicle registration code for the German city of Salzgitter in Lower Saxony.
  • E. SVJ
    SVJ is the three-letter IATA airport code for Svolvær Airport, Helle in Norway.
  • 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: SŽ
Triple: [Správa železnic, abbreviation, SŽ]
Generated description
SŽ is the Czech national railway infrastructure manager responsible for operating, maintaining, and developing the country’s railway network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SŽ
Target entity description: SŽ is the Czech national railway infrastructure manager responsible for operating, maintaining, and developing the country’s railway network.
  • A. 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.
  • B. SZĽH
    SZĽH is the Slovak Ice Hockey Federation, the governing body responsible for organizing and overseeing ice hockey activities and national teams in Slovakia.
  • C. SZ
    SZ is the official station code used to identify the Berlin U-Bahn station Seestraße.
  • D. SZ
    SZ is the vehicle registration code for the German city of Salzgitter in Lower Saxony.
  • E. SVJ
    SVJ is the three-letter IATA airport code for Svolvær Airport, Helle in Norway.
  • 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_69d8dcfd05bc819088903cca13cc2846 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c52eed1881908929dace845ae008 completed April 20, 2026, 6:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0582c196888190aa49b219aedb06e2 completed May 14, 2026, 8:07 a.m.
NEDg Description generation batch_6a05890d8a1c819081ad3d12ea9c4d5e completed May 14, 2026, 8:34 a.m.
NED2 Entity disambiguation (via description) batch_6a0589a3c0c08190be4b6dd6e9a56fdb completed May 14, 2026, 8:36 a.m.
Created at: April 10, 2026, 11:58 a.m.