Triple

T6348572
Position Surface form Disambiguated ID Type / Status
Subject Berlin–Blankenheim railway E142807 entity
Predicate endPoint P390 FINISHED
Object Blankenheim E594272 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: Blankenheim | Statement: [Berlin–Blankenheim railway, endPoint, Blankenheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blankenheim
Context triple: [Berlin–Blankenheim railway, endPoint, Blankenheim]
  • A. Blankenheim chosen
    Blankenheim is a municipality in western Germany, known for its historic town center and location in the Eifel region of North Rhine-Westphalia.
  • B. Brackenheim
    Brackenheim is a small town in the German state of Baden-Württemberg, best known as the birthplace of Theodor Heuss, the first President of the Federal Republic of Germany.
  • C. Bergheim
    Bergheim is a municipality in the Austrian state of Salzburg, located just north of the city of Salzburg and known for its suburban character and proximity to the regional capital.
  • D. Rolandseck
    Rolandseck is a district of Remagen in Rhineland-Palatinate, Germany, known for its scenic location on the Rhine and its historic railway station and cultural venues.
  • E. Landsberg
    Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
  • 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_69c008d6dcbc8190aa1c2f1fd8916b42 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c067bba1988190b51f0a22e4279e1b completed March 22, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69c65381ab8081908293225471062f28 completed March 27, 2026, 9:53 a.m.
Created at: March 22, 2026, 4:31 p.m.