Triple

T16972454
Position Surface form Disambiguated ID Type / Status
Subject Berlin-Westkreuz station E411719 entity
Predicate servedByLine P1293 FINISHED
Object S3
S3 is a line of the Berlin S-Bahn rapid transit network that connects various suburbs with central Berlin.
 E142486 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: S3 | Statement: [Berlin-Westkreuz station, servedByLine, S3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: S3
Context triple: [Berlin-Westkreuz station, servedByLine, S3]
  • A. S3
    S3 is a commuter rail line of the Stuttgart S-Bahn network in Germany, connecting the city center with surrounding suburban areas.
  • B. S3
    S3 is one of the commuter rail lines of the Nuremberg S-Bahn network in Germany, serving regional passenger traffic between the city and its surrounding areas.
  • C. S3
    S3 is a line of the Munich S-Bahn suburban rail network that connects central Munich with its surrounding metropolitan area.
  • D. S3
    S3 is a commuter rail line within Germany’s Rhine-Ruhr S-Bahn network, serving regional passenger traffic across the metropolitan area.
  • E. S3
    S3 is a regional S-Bahn train line in the Rhine-Main area of Germany that connects central Frankfurt with surrounding suburbs and towns.
  • 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: S3
Triple: [Berlin-Westkreuz station, servedByLine, S3]
Generated description
S3 is a line of the Berlin S-Bahn rapid transit network that connects various suburbs with central Berlin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: S3
Target entity description: S3 is a line of the Berlin S-Bahn rapid transit network that connects various suburbs with central Berlin.
  • A. S3 chosen
    S3 is a line of the Berlin S-Bahn urban rail network that connects various districts across the Berlin metropolitan area.
  • B. S3
    S3 is a line of the Munich S-Bahn suburban rail network that connects central Munich with its surrounding metropolitan area.
  • C. S3
    S3 is a regional S-Bahn train line in the Rhine-Main area of Germany that connects central Frankfurt with surrounding suburbs and towns.
  • D. S3
    S3 is a commuter rail line of the Stuttgart S-Bahn network in Germany, connecting the city center with surrounding suburban areas.
  • E. S3
    S3 is a commuter rail line within Germany’s Rhine-Ruhr S-Bahn network, serving regional passenger traffic across the metropolitan area.
  • F. None of above.

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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d0ae47f08190a13e98d20aba7f16 completed April 18, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d471d4248190acf40b6c11926a65 completed May 10, 2026, 6:54 p.m.
NEDg Description generation batch_6a00d503f4f08190a0dcdb050d5bc7a3 completed May 10, 2026, 6:57 p.m.
NED2 Entity disambiguation (via description) batch_6a00d5adee908190a13bfc765e7c8f06 completed May 10, 2026, 6:59 p.m.
Created at: April 10, 2026, 5:31 a.m.