Triple

T20960005
Position Surface form Disambiguated ID Type / Status
Subject Hamburg S-Bahn E516213 entity
Predicate hasLine P35 FINISHED
Object S11
S11 is a suburban rail line of the Hamburg S-Bahn network serving various districts in and around Hamburg, Germany.
 E1460126 NE FINISHED

How this triple was built (4 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: S11 | Statement: [Hamburg S-Bahn, hasLine, S11]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: S11
Context triple: [Hamburg S-Bahn, hasLine, S11]
  • A. S11
    S11 is a commuter rail line within Germany’s Rhine-Ruhr S-Bahn network, serving regional passenger traffic across the metropolitan area.
  • B. S1
    S1 is a key commuter rail line of the Berlin S-Bahn network, connecting central Berlin with its northern and southwestern suburbs.
  • C. S1
    S1 is a regional S-Bahn rail line within Germany’s Rhine-Ruhr metropolitan transit network, connecting key cities and suburbs in the area.
  • D. S1
    S1 is a rapid transit line of the Hamburg S-Bahn network in Germany, connecting key suburbs with central Hamburg.
  • E. S1
    S1 is a commuter rail line within the Rhine-Main S-Bahn network serving the Frankfurt metropolitan region in Germany.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: S11
Triple: [Hamburg S-Bahn, hasLine, S11]
Generated description
S11 is a suburban rail line of the Hamburg S-Bahn network serving various districts in and around Hamburg, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: S11
Target entity description: S11 is a suburban rail line of the Hamburg S-Bahn network serving various districts in and around Hamburg, Germany.
  • A. S11
    S11 is a commuter rail line within Germany’s Rhine-Ruhr S-Bahn network, serving regional passenger traffic across the metropolitan area.
  • B. S1
    S1 is a regional S-Bahn rail line within Germany’s Rhine-Ruhr metropolitan transit network, connecting key cities and suburbs in the area.
  • C. S1
    S1 is a key commuter rail line of the Berlin S-Bahn network, connecting central Berlin with its northern and southwestern suburbs.
  • D. S1
    S1 is a rapid transit line of the Hamburg S-Bahn network in Germany, connecting key suburbs with central Hamburg.
  • E. S1
    S1 is a commuter rail line within the Rhine-Main S-Bahn network serving the Frankfurt metropolitan region in Germany.
  • F. None of above. chosen

Provenance (5 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_69e0b4fde6c48190af1398e7e734629e completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fb6e50988190a564d2aaf1a9bc54 completed April 21, 2026, 4:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a092faf16b0819097a3eeee0155a3dd completed May 17, 2026, 3:02 a.m.
NEDg Description generation batch_6a0930490b3481908e11810632652af6 completed May 17, 2026, 3:04 a.m.
NED2 Entity disambiguation (via description) batch_6a0930ac06b08190b319d9b779897977 completed May 17, 2026, 3:06 a.m.
Created at: April 16, 2026, 1:30 p.m.