Triple

T21513335
Position Surface form Disambiguated ID Type / Status
Subject U8 E530781 entity
Predicate hasStation P35 FINISHED
Object Rosenthaler Platz
Rosenthaler Platz is a central Berlin U-Bahn station and busy traffic hub in the Mitte district, known for its surrounding cafés, nightlife, and creative scene.
E1498191 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: Rosenthaler Platz | Statement: [U8, hasStation, Rosenthaler Platz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosenthaler Platz
Context triple: [U8, hasStation, Rosenthaler Platz]
  • A. Kaulbachplatz
    Kaulbachplatz is an underground station on Munich’s U-Bahn network, serving the U3 line in the Schwabing district.
  • B. Nachtigalplatz
    Nachtigalplatz is a public square in Berlin’s Afrikanisches Viertel, known for its controversial colonial-era namesake and its role in debates over decolonizing urban toponymy.
  • C. Nauener Platz
    Nauener Platz is a Berlin U-Bahn station on the U9 line located in the Wedding district of the city.
  • D. Lehniner Platz
    Lehniner Platz is a public square in Berlin, Germany, known as a cultural hub and transport node in the Charlottenburg district.
  • E. Kollwitzplatz
    Kollwitzplatz is a well-known square and cultural hub in Berlin’s Prenzlauer Berg district, noted for its lively markets, cafés, and historic architecture.
  • 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: Rosenthaler Platz
Triple: [U8, hasStation, Rosenthaler Platz]
Generated description
Rosenthaler Platz is a central Berlin U-Bahn station and busy traffic hub in the Mitte district, known for its surrounding cafés, nightlife, and creative scene.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rosenthaler Platz
Target entity description: Rosenthaler Platz is a central Berlin U-Bahn station and busy traffic hub in the Mitte district, known for its surrounding cafés, nightlife, and creative scene.
  • A. Kaulbachplatz
    Kaulbachplatz is an underground station on Munich’s U-Bahn network, serving the U3 line in the Schwabing district.
  • B. Nachtigalplatz
    Nachtigalplatz is a public square in Berlin’s Afrikanisches Viertel, known for its controversial colonial-era namesake and its role in debates over decolonizing urban toponymy.
  • C. Nauener Platz
    Nauener Platz is a Berlin U-Bahn station on the U9 line located in the Wedding district of the city.
  • D. Lehniner Platz
    Lehniner Platz is a public square in Berlin, Germany, known as a cultural hub and transport node in the Charlottenburg district.
  • E. Kollwitzplatz
    Kollwitzplatz is a well-known square and cultural hub in Berlin’s Prenzlauer Berg district, noted for its lively markets, cafés, and historic architecture.
  • 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_69e0c45c81f08190a6b8bbb70a45aae7 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea88e6fc8190a4b73b8d32dae5a8 completed April 23, 2026, 9:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0a24990c548190b8d4125b896683ff completed May 17, 2026, 8:27 p.m.
NEDg Description generation batch_6a0a25e3f88c8190b9e45419c281f781 completed May 17, 2026, 8:32 p.m.
NED2 Entity disambiguation (via description) batch_6a0a26ad254081908be75936046e23ca completed May 17, 2026, 8:35 p.m.
Created at: April 16, 2026, 6:25 p.m.