Triple

T3825939
Position Surface form Disambiguated ID Type / Status
Subject Tram line 7 (VBZ) E88689 entity
Predicate fareSystem P395 FINISHED
Object ZVV
ZVV is the Zürcher Verkehrsverbund, the integrated public transport network and fare association for the Zurich metropolitan area in Switzerland.
 E390723 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: ZVV | Statement: [Tram line 7 (VBZ), fareSystem, ZVV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ZVV
Context triple: [Tram line 7 (VBZ), fareSystem, ZVV]
  • A. EV Zug
    EV Zug is a professional ice hockey club from Zug, Switzerland, known as one of the prominent teams in the country’s top-tier league.
  • B. ZVVZ USK Praha
    ZVVZ USK Praha is a prominent Czech women's basketball club based in Prague that competes at the top level of domestic and European competitions.
  • C. BZZ
    BZZ is the IATA airport code for RAF Brize Norton, a major Royal Air Force transport and air-to-air refuelling base in Oxfordshire, England.
  • D. BVG
    BVG is Berlin’s main public transport company, operating the city’s U-Bahn, trams, buses, and ferries.
  • E. ZZ
    ZZ is an aircraft registration prefix used to identify certain aircraft, such as those in the Voyager KC2 fleet.
  • 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: ZVV
Triple: [Tram line 7 (VBZ), fareSystem, ZVV]
Generated description
ZVV is the Zürcher Verkehrsverbund, the integrated public transport network and fare association for the Zurich metropolitan area in Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ZVV
Target entity description: ZVV is the Zürcher Verkehrsverbund, the integrated public transport network and fare association for the Zurich metropolitan area in Switzerland.
  • A. EV Zug
    EV Zug is a professional ice hockey club from Zug, Switzerland, known as one of the prominent teams in the country’s top-tier league.
  • B. ZVVZ USK Praha
    ZVVZ USK Praha is a prominent Czech women's basketball club based in Prague that competes at the top level of domestic and European competitions.
  • C. BZZ
    BZZ is the IATA airport code for RAF Brize Norton, a major Royal Air Force transport and air-to-air refuelling base in Oxfordshire, England.
  • D. BVG
    BVG is Berlin’s main public transport company, operating the city’s U-Bahn, trams, buses, and ferries.
  • E. ZZ
    ZZ is an aircraft registration prefix used to identify certain aircraft, such as those in the Voyager KC2 fleet.
  • 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_69aed9538cf881909d9ce8ca4ac7c18c completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeeb6364fc8190bf8401743f1695d5 completed March 9, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb4f41c88190b3040236462c37cc completed March 14, 2026, 6:08 a.m.
NEDg Description generation batch_69b4fc9fc5dc81908772fc642285abf6 completed March 14, 2026, 6:13 a.m.
NED2 Entity disambiguation (via description) batch_69b4fd0dc3d48190b907d7a1c1e44066 completed March 14, 2026, 6:15 a.m.
Created at: March 9, 2026, 3:17 p.m.