Triple

T8714998
Position Surface form Disambiguated ID Type / Status
Subject Munich S-Bahn trunk line E206870 entity
Predicate usedBy P260 FINISHED
Object S4
S4 is a line of the Munich S-Bahn rapid transit network that runs through the central trunk route and connects Munich with its surrounding suburbs.
 E754932 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: S4 | Statement: [Munich S-Bahn trunk line, usedBy, S4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: S4
Context triple: [Munich S-Bahn trunk line, usedBy, S4]
  • A. S4
    S4 is a commuter rail line of the Nuremberg S-Bahn network serving regional passenger traffic in and around Nuremberg, Germany.
  • B. S4
    S4 is a commuter rail line of the Stuttgart S-Bahn network serving the Stuttgart metropolitan area in Germany.
  • C. S44
    S44 is a Staten Island local bus route in New York City that connects New Springville with other neighborhoods across the borough.
  • D. S45
    S45 is the FAA location identifier for Siletz Bay State Airport, a public airport serving the Lincoln City area in Oregon, United States.
  • E. S45
    S45 is a Berlin S-Bahn suburban rail line that connects the city’s southern districts, including Berlin Brandenburg Airport, with the wider urban transit network.
  • 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: S4
Triple: [Munich S-Bahn trunk line, usedBy, S4]
Generated description
S4 is a line of the Munich S-Bahn rapid transit network that runs through the central trunk route and connects Munich with its surrounding suburbs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: S4
Target entity description: S4 is a line of the Munich S-Bahn rapid transit network that runs through the central trunk route and connects Munich with its surrounding suburbs.
  • A. S4
    S4 is a commuter rail line of the Nuremberg S-Bahn network serving regional passenger traffic in and around Nuremberg, Germany.
  • B. S4
    S4 is a commuter rail line of the Stuttgart S-Bahn network serving the Stuttgart metropolitan area in Germany.
  • C. S44
    S44 is a Staten Island local bus route in New York City that connects New Springville with other neighborhoods across the borough.
  • D. S45
    S45 is the FAA location identifier for Siletz Bay State Airport, a public airport serving the Lincoln City area in Oregon, United States.
  • E. S45
    S45 is a Berlin S-Bahn suburban rail line that connects the city’s southern districts, including Berlin Brandenburg Airport, with the wider urban transit network.
  • 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_69ca83572d4881909bef3be2b578d539 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5cd6707c819092c9fca34f273d5e completed March 31, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf42998df88190a6eba28c2efb2030 completed April 3, 2026, 4:31 a.m.
NEDg Description generation batch_69cf448b65a88190944689160e734866 completed April 3, 2026, 4:39 a.m.
NED2 Entity disambiguation (via description) batch_69cf4578473081909fc55632c366a56a completed April 3, 2026, 4:43 a.m.
Created at: March 30, 2026, 6:35 p.m.