Triple

T20023193
Position Surface form Disambiguated ID Type / Status
Subject Czech Railways E494911 entity
Predicate cooperatesWith P435 FINISHED
Object ZSSK
ZSSK (Železničná spoločnosť Slovensko) is Slovakia’s state-owned passenger railway operator, providing domestic and international train services across the country and beyond.
 E1406807 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: ZSSK | Statement: [Czech Railways, cooperatesWith, ZSSK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ZSSK
Context triple: [Czech Railways, cooperatesWith, ZSSK]
  • A. ZSSS
    ZSSS is the ICAO airport code for Shanghai Hongqiao International Airport, a major domestic and regional aviation hub in Shanghai, China.
  • B. ZSC
    ZSC is a Swiss professional ice hockey club based in Zürich that competes in the National League.
  • C. ZS
    ZS is the stock ticker symbol for Zscaler, a cloud-based information security company traded on the NASDAQ.
  • D. ZS
    ZS is the vehicle registration code assigned to cars registered in the Polish city of Szczecin.
  • E. ZK
    ZK is the vehicle registration code used for vehicles registered in the city of Zakynthos in Greece.
  • 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: ZSSK
Triple: [Czech Railways, cooperatesWith, ZSSK]
Generated description
ZSSK (Železničná spoločnosť Slovensko) is Slovakia’s state-owned passenger railway operator, providing domestic and international train services across the country and beyond.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ZSSK
Target entity description: ZSSK (Železničná spoločnosť Slovensko) is Slovakia’s state-owned passenger railway operator, providing domestic and international train services across the country and beyond.
  • A. ZSSS
    ZSSS is the ICAO airport code for Shanghai Hongqiao International Airport, a major domestic and regional aviation hub in Shanghai, China.
  • B. ZSC
    ZSC is a Swiss professional ice hockey club based in Zürich that competes in the National League.
  • C. ZS
    ZS is the vehicle registration code assigned to cars registered in the Polish city of Szczecin.
  • D. ZS
    ZS is the stock ticker symbol for Zscaler, a cloud-based information security company traded on the NASDAQ.
  • E. ZK
    ZK is the vehicle registration code used for vehicles registered in the city of Zakynthos in Greece.
  • 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6628a1ecc8190bf6ee0bedb61e0b8 completed April 20, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a080e2d32008190a770addba6e44adb completed May 16, 2026, 6:26 a.m.
NEDg Description generation batch_6a080ec9c56481908b69834b5a1ae105 completed May 16, 2026, 6:29 a.m.
NED2 Entity disambiguation (via description) batch_6a080f6e218c8190b4c7b0d5de9f984c completed May 16, 2026, 6:32 a.m.
Created at: April 11, 2026, 3:35 p.m.