Triple

T20667873
Position Surface form Disambiguated ID Type / Status
Subject Munich S-Bahn E507939 entity
Predicate hasLine P35 FINISHED
Object S7
S7 is a line of the Munich S-Bahn rapid transit network serving suburban and regional routes in and around Munich, Germany.
E1444676 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: S7 | Statement: [Munich S-Bahn, hasLine, S7]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S7
Context triple: [Munich S-Bahn, hasLine, S7]
  • A. S7
    S7 is a line of the Rhine-Main S-Bahn rapid transit network serving the Frankfurt Rhine-Main metropolitan region in Germany.
  • B. S7
    S7 is a regional rail service designation within the RER Vaud network in Switzerland, operating as one of its numbered commuter train lines.
  • C. S7
    S7 is a Berlin S-Bahn rapid transit line that runs across the city, connecting key districts between Potsdam and Ahrensfelde.
  • D. S7
    S7 is the IATA airline designator for S7 Airlines, a major Russian carrier based in Novosibirsk.
  • E. S75
    S75 is a line of the Berlin S-Bahn urban rail network serving routes within the Berlin metropolitan area.
  • 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: S7
Triple: [Munich S-Bahn, hasLine, S7]
Generated description
S7 is a line of the Munich S-Bahn rapid transit network serving suburban and regional routes in and around Munich, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: S7
Target entity description: S7 is a line of the Munich S-Bahn rapid transit network serving suburban and regional routes in and around Munich, Germany.
  • A. S7
    S7 is a Berlin S-Bahn rapid transit line that runs across the city, connecting key districts between Potsdam and Ahrensfelde.
  • B. S7
    S7 is the IATA airline designator for S7 Airlines, a major Russian carrier based in Novosibirsk.
  • C. S7
    S7 is a line of the Rhine-Main S-Bahn rapid transit network serving the Frankfurt Rhine-Main metropolitan region in Germany.
  • D. S7
    S7 is a regional rail service designation within the RER Vaud network in Switzerland, operating as one of its numbered commuter train lines.
  • E. S75
    S75 is a line of the Berlin S-Bahn urban rail network serving routes within the Berlin metropolitan area.
  • 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_69e0b4c059bc81908ea762cd73ea4424 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6b5c4c4608190ae17da4a59e5ae80 completed April 20, 2026, 11:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08cd6271e481909e3a6f10ec40ce11 completed May 16, 2026, 8:02 p.m.
NEDg Description generation batch_6a08d175eefc8190a5178c0f70f7d79f completed May 16, 2026, 8:20 p.m.
NED2 Entity disambiguation (via description) batch_6a08d23e8ac48190be1726c8e4913b1a completed May 16, 2026, 8:23 p.m.
Created at: April 16, 2026, 11:44 a.m.