Triple

T11904331
Position Surface form Disambiguated ID Type / Status
Subject Stuttgart Stadtbahn E283234 entity
Predicate hasLine P35 FINISHED
Object U13E
U13E is a specific line of the Stuttgart Stadtbahn light rail network serving urban transit routes within Stuttgart, Germany.
 E953844 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: U13E | Statement: [Stuttgart Stadtbahn, hasLine, U13E]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: U13E
Context triple: [Stuttgart Stadtbahn, hasLine, U13E]
  • A. UWC-136
    UWC-136 is a mobile telecommunications standard within the IMT-2000 family designed to support third-generation (3G) wireless services.
  • B. U1
    U1 is a major line of the Vienna U-Bahn rapid transit system, running in a north–south direction and connecting key districts across the city.
  • C. U1
    U1 is a major line of the Nuremberg U-Bahn rapid transit system, connecting key districts across the Nuremberg metropolitan area.
  • D. U1
    U1 is one of Berlin’s oldest and most central U-Bahn lines, running predominantly east–west through inner-city districts and serving key cultural and nightlife areas.
  • E. U1
    U1 is a major line of the Munich U-Bahn rapid transit system, running through key districts of the city and connecting important residential and commercial areas.
  • 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: U13E
Triple: [Stuttgart Stadtbahn, hasLine, U13E]
Generated description
U13E is a specific line of the Stuttgart Stadtbahn light rail network serving urban transit routes within Stuttgart, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: U13E
Target entity description: U13E is a specific line of the Stuttgart Stadtbahn light rail network serving urban transit routes within Stuttgart, Germany.
  • A. UWC-136
    UWC-136 is a mobile telecommunications standard within the IMT-2000 family designed to support third-generation (3G) wireless services.
  • B. U1
    U1 is a major line of the Vienna U-Bahn rapid transit system, running in a north–south direction and connecting key districts across the city.
  • C. U1
    U1 is a major line of the Nuremberg U-Bahn rapid transit system, connecting key districts across the Nuremberg metropolitan area.
  • D. U1
    U1 is one of Berlin’s oldest and most central U-Bahn lines, running predominantly east–west through inner-city districts and serving key cultural and nightlife areas.
  • E. U1
    U1 is a major line of the Munich U-Bahn rapid transit system, running through key districts of the city and connecting important residential and commercial areas.
  • 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e525460c81909d855048d9c799bf completed April 10, 2026, 11:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69f418487f448190b6e24fb2c0409e3f completed May 1, 2026, 3:04 a.m.
NEDg Description generation batch_69f41f1d2da0819082f00cf61a6530b6 completed May 1, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69f4228a73708190a6d2db321e175921 completed May 1, 2026, 3:48 a.m.
Created at: April 8, 2026, 9:44 p.m.