Triple

T22183605
Position Surface form Disambiguated ID Type / Status
Subject Vienna S-Bahn E548233 entity
Predicate hasLine P35 FINISHED
Object S7
S7 is a commuter rail line of the Vienna S-Bahn network that connects central Vienna with Vienna International Airport and surrounding regions.
 E1523365 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: [Vienna S-Bahn, hasLine, S7]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: S7
Context triple: [Vienna S-Bahn, hasLine, S7]
  • A. S7
    S7 is a line of the Munich S-Bahn rapid transit network serving suburban and regional routes in and around Munich, Germany.
  • B. S7
    S7 is a Berlin S-Bahn rapid transit line that runs across the city, connecting key districts between Potsdam and Ahrensfelde.
  • C. S7
    S7 is the IATA airline designator for S7 Airlines, a major Russian carrier based in Novosibirsk.
  • D. S7
    S7 is a line of the Rhine-Main S-Bahn rapid transit network serving the Frankfurt Rhine-Main metropolitan region in Germany.
  • E. S7
    S7 is a regional rail service designation within the RER Vaud network in Switzerland, operating as one of its numbered commuter train lines.
  • 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: [Vienna S-Bahn, hasLine, S7]
Generated description
S7 is a commuter rail line of the Vienna S-Bahn network that connects central Vienna with Vienna International Airport and surrounding regions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: S7
Target entity description: S7 is a commuter rail line of the Vienna S-Bahn network that connects central Vienna with Vienna International Airport and surrounding regions.
  • 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. S7
    S7 is a line of the Munich S-Bahn rapid transit network serving suburban and regional routes in and around Munich, 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_69e11e3e0c7c8190b30d278845e2497e completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12aa75440819084cbe9176b9edb47 completed April 28, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a9ecd0a7881909dbda649b8474ff1 completed May 18, 2026, 5:08 a.m.
NEDg Description generation batch_6a0a9f494f3c8190aee8f2e6dc1af763 completed May 18, 2026, 5:10 a.m.
NED2 Entity disambiguation (via description) batch_6a0aa03a8e0c819089dc48473b5b743c completed May 18, 2026, 5:14 a.m.
Created at: April 16, 2026, 8:35 p.m.