Triple

T3390442
Position Surface form Disambiguated ID Type / Status
Subject Leopoldplatz E71403 entity
Predicate hasNearbyStreet P8235 FINISHED
Object Müllerstraße
Müllerstraße is a major thoroughfare in Berlin’s Wedding district, known for its dense urban character, shops, and public transport connections.
 E376992 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: Müllerstraße | Statement: [Leopoldplatz, hasNearbyStreet, Müllerstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Müllerstraße
Context triple: [Leopoldplatz, hasNearbyStreet, Müllerstraße]
  • A. Scharnweberstraße
    Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • B. Kaufingerstraße
    Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
  • C. Braubachstraße
    Braubachstraße is a historic street in Frankfurt’s Altstadt known for its traditional architecture, shops, and proximity to key cultural and tourist sites.
  • D. Schwartzkopffstraße
    Schwartzkopffstraße is a Berlin U-Bahn station on the U6 line located in the central district of the city.
  • E. Yorckstraße
    Yorckstraße is a major street and transport corridor in Berlin’s Kreuzberg and Schöneberg districts, known for its multiple S-Bahn stations and proximity to several historic cemeteries and railway viaducts.
  • 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: Müllerstraße
Triple: [Leopoldplatz, hasNearbyStreet, Müllerstraße]
Generated description
Müllerstraße is a major thoroughfare in Berlin’s Wedding district, known for its dense urban character, shops, and public transport connections.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Müllerstraße
Target entity description: Müllerstraße is a major thoroughfare in Berlin’s Wedding district, known for its dense urban character, shops, and public transport connections.
  • A. Scharnweberstraße
    Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • B. Kaufingerstraße
    Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
  • C. Braubachstraße
    Braubachstraße is a historic street in Frankfurt’s Altstadt known for its traditional architecture, shops, and proximity to key cultural and tourist sites.
  • D. Schwartzkopffstraße
    Schwartzkopffstraße is a Berlin U-Bahn station on the U6 line located in the central district of the city.
  • E. Yorckstraße
    Yorckstraße is a major street and transport corridor in Berlin’s Kreuzberg and Schöneberg districts, known for its multiple S-Bahn stations and proximity to several historic cemeteries and railway viaducts.
  • 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_69ad85a9c4a88190a854019341cb3b60 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb6682c708190b76a7a16cee7c5aa completed March 8, 2026, 5:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4881cd6f081908981db17758146f7 completed March 13, 2026, 9:56 p.m.
NEDg Description generation batch_69b48a9a55fc8190bc7de7c2c1e9bf76 completed March 13, 2026, 10:07 p.m.
NED2 Entity disambiguation (via description) batch_69b4a3d9377481909bc0392a1176601b completed March 13, 2026, 11:55 p.m.
Created at: March 8, 2026, 3:14 p.m.