Triple

T14266184
Position Surface form Disambiguated ID Type / Status
Subject U9 E353649 entity
Predicate hasStation P35 FINISHED
Object Hansaplatz
Hansaplatz is a Berlin U-Bahn station on the U9 line located in the Hansaviertel district of the city.
E1093639 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: Hansaplatz | Statement: [U9, hasStation, Hansaplatz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hansaplatz
Context triple: [U9, hasStation, Hansaplatz]
  • A. Roncalliplatz
    Roncalliplatz is a central public square in Cologne, Germany, situated by Cologne Cathedral and home to major cultural sites and events.
  • B. Odeonsplatz
    Odeonsplatz is a large historic square in central Munich, Germany, known for its grand architecture and role as a prominent cultural and political gathering place.
  • C. Marijinplatz
    Marijinplatz is the former name of Ljubljana’s central Prešeren Square, a key cultural and social gathering place in Slovenia’s capital.
  • D. Alter Platz
    Alter Platz is the historic main square in Klagenfurt, Austria, known for its traditional architecture, shops, and cafés.
  • E. Schinkelplatz
    Schinkelplatz is a historic square in central Berlin named after architect Karl Friedrich Schinkel, known for its neoclassical surroundings and proximity to major cultural and governmental buildings.
  • 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: Hansaplatz
Triple: [U9, hasStation, Hansaplatz]
Generated description
Hansaplatz is a Berlin U-Bahn station on the U9 line located in the Hansaviertel district of the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hansaplatz
Target entity description: Hansaplatz is a Berlin U-Bahn station on the U9 line located in the Hansaviertel district of the city.
  • A. Roncalliplatz
    Roncalliplatz is a central public square in Cologne, Germany, situated by Cologne Cathedral and home to major cultural sites and events.
  • B. Odeonsplatz
    Odeonsplatz is a large historic square in central Munich, Germany, known for its grand architecture and role as a prominent cultural and political gathering place.
  • C. Marijinplatz
    Marijinplatz is the former name of Ljubljana’s central Prešeren Square, a key cultural and social gathering place in Slovenia’s capital.
  • D. Alter Platz
    Alter Platz is the historic main square in Klagenfurt, Austria, known for its traditional architecture, shops, and cafés.
  • E. Schinkelplatz
    Schinkelplatz is a historic square in central Berlin named after architect Karl Friedrich Schinkel, known for its neoclassical surroundings and proximity to major cultural and governmental buildings.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6358c2288190ac1fd26e688a605d completed April 14, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd467d45c88190ac6ac280aa691591 completed May 8, 2026, 2:12 a.m.
NEDg Description generation batch_69fd4811e2808190b559d8348079ae8f completed May 8, 2026, 2:18 a.m.
NED2 Entity disambiguation (via description) batch_69fd48d827488190b4a494d4da64ba51 completed May 8, 2026, 2:22 a.m.
Created at: April 10, 2026, 1:09 a.m.