Triple

T3824834
Position Surface form Disambiguated ID Type / Status
Subject VGN fare zone 200 E88660 entity
Predicate includes P1393 FINISHED
Object Fürth Hauptbahnhof E15519 NE FINISHED

How this triple was built (2 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: Fürth Hauptbahnhof | Statement: [VGN fare zone 200, includes, Fürth Hauptbahnhof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fürth Hauptbahnhof
Context triple: [VGN fare zone 200, includes, Fürth Hauptbahnhof]
  • A. Fürth Hauptbahnhof chosen
    Fürth Hauptbahnhof is the main railway station of Fürth in Bavaria, Germany, serving as a regional and local transport hub with connections to nearby cities including Nuremberg.
  • B. Graz Hauptbahnhof
    Graz Hauptbahnhof is the main railway station and central transport hub of the city of Graz in Austria.
  • C. Bern Hauptbahnhof
    Bern Hauptbahnhof is the main railway station in Switzerland’s capital city, serving as a major national and international transport hub.
  • D. Vienna station
    Vienna station is a Washington Metro rapid transit station in Fairfax County, Virginia, serving as the western endpoint of the system’s Orange Line.
  • E. Praterstern railway station
    Praterstern railway station is a major transport hub in Vienna, Austria, serving as a key interchange for regional and urban rail, metro, tram, and bus services.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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.
Created at: March 9, 2026, 3:17 p.m.