Triple

T754328
Position Surface form Disambiguated ID Type / Status
Subject Fürth Hauptbahnhof E15519 entity
Predicate connectsToCity P4245 FINISHED
Object Bamberg E134924 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: Bamberg | Statement: [Fürth Hauptbahnhof, connectsToCity, Bamberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bamberg
Context triple: [Fürth Hauptbahnhof, connectsToCity, Bamberg]
  • A. Bamberg chosen
    Bamberg is a historic city in northern Bavaria, Germany, renowned for its well-preserved medieval old town and status as a UNESCO World Heritage Site.
  • B. Coburg
    Coburg is a historic town in northern Bavaria, Germany, known for its well-preserved medieval architecture and its former role as the seat of the Duchy of Saxe-Coburg and Gotha.
  • C. Regensburg
    Regensburg is a historic city in southeastern Germany known for its well-preserved medieval old town on the Danube River.
  • D. Würzburg
    Würzburg is a historic city in southern Germany known for its baroque architecture, the Würzburg Residence palace, and its location along the Main River in the Franconia wine region.
  • E. Augsburg
    Augsburg is one of Germany’s oldest cities, a historic Bavarian center known for its rich Renaissance heritage and role as a major medieval trading hub.
  • 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_69a493599a0081908da65f3407af1ef2 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aa9ba3888190889a1ad554f73c5e completed March 1, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae589ab1b48190bb10fd42a48ea0fe completed March 9, 2026, 5:20 a.m.
Created at: March 1, 2026, 7:37 p.m.