Triple

T16387802
Position Surface form Disambiguated ID Type / Status
Subject S42 (Berlin S-Bahn line) E397967 entity
Predicate majorInterchangeStation P30882 FINISHED
Object Südkreuz E590407 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: Südkreuz | Statement: [S42 (Berlin S-Bahn line), majorInterchangeStation, Südkreuz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Südkreuz
Context triple: [S42 (Berlin S-Bahn line), majorInterchangeStation, Südkreuz]
  • A. Südkreuz chosen
    Südkreuz is a major Berlin railway and transport interchange that serves as one of the city’s key regional, long-distance, and urban transit stations.
  • B. Spiegelrei
    Spiegelrei is a picturesque historic canal quay in Bruges, Belgium, known for its medieval architecture and scenic waterfront views.
  • C. Sternschanze
    Sternschanze is a trendy Hamburg neighborhood known for its alternative culture, vibrant nightlife, and street art.
  • D. Ostkreuz
    Ostkreuz is one of Berlin’s busiest and most important S-Bahn interchange stations, serving as a major hub for multiple suburban rail lines.
  • E. Dinkelscherben
    Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
  • 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e3263e1534819081a6bf5006c611c5 completed April 18, 2026, 6:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00356ed47c819085aaf101459dd55c completed May 10, 2026, 7:36 a.m.
Created at: April 10, 2026, 5:08 a.m.