Triple

T8476507
Position Surface form Disambiguated ID Type / Status
Subject Leipzig Hauptbahnhof E200406 entity
Predicate hasName P744 FINISHED
Object Leipzig Hauptbahnhof E200406 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: Leipzig Hauptbahnhof | Statement: [Leipzig Hauptbahnhof, hasName, Leipzig Hauptbahnhof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leipzig Hauptbahnhof
Context triple: [Leipzig Hauptbahnhof, hasName, Leipzig Hauptbahnhof]
  • A. Dresden Hauptbahnhof
    Dresden Hauptbahnhof is the main central railway station of Dresden, Germany, serving as a major regional and long-distance transport hub.
  • B. Magdeburg Hauptbahnhof
    Magdeburg Hauptbahnhof is the main railway station and central transport hub of the city of Magdeburg in Saxony-Anhalt, Germany.
  • C. Leipzig Hauptbahnhof (main railway station) chosen
    Leipzig Hauptbahnhof is one of Europe’s largest terminal railway stations, serving as a major transportation hub and commercial center in Leipzig, Germany.
  • D. Hannover Hauptbahnhof
    Hannover Hauptbahnhof is the main central railway station of Hanover, Germany, serving as a major national and international transport hub.
  • E. Nürnberg Hauptbahnhof
    Nürnberg Hauptbahnhof is the main railway station and a central public transport hub in Nuremberg, Germany, serving regional, long-distance, and urban transit including the U-Bahn network.
  • 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_69ca831b17988190a1f3f3413d57b820 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe51e21548190811e3c7ba7b196e5 completed March 31, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce3a196ad48190b3887a2a0c43f87f completed April 2, 2026, 9:42 a.m.
Created at: March 30, 2026, 6:12 p.m.