Triple

T3848717
Position Surface form Disambiguated ID Type / Status
Subject Akazienkiez E85236 entity
Predicate hasStreet P959 FINISHED
Object Grunewaldstraße
Grunewaldstraße is a notable street in Berlin’s Akazienkiez neighborhood, known for its mix of residential buildings, local shops, and cafés.
 E430192 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: Grunewaldstraße | Statement: [Akazienkiez, hasStreet, Grunewaldstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Grunewaldstraße
Context triple: [Akazienkiez, hasStreet, Grunewaldstraße]
  • A. Chausseestraße
    Chausseestraße is a major historic street in Berlin, Germany, known for its cultural landmarks and central location.
  • 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. Scharnweberstraße
    Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • D. Paradestraße
    Paradestraße is a Berlin U-Bahn station on the north–south route in the Tempelhof-Schöneberg district, known for serving the U6 line.
  • 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: Grunewaldstraße
Triple: [Akazienkiez, hasStreet, Grunewaldstraße]
Generated description
Grunewaldstraße is a notable street in Berlin’s Akazienkiez neighborhood, known for its mix of residential buildings, local shops, and cafés.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Grunewaldstraße
Target entity description: Grunewaldstraße is a notable street in Berlin’s Akazienkiez neighborhood, known for its mix of residential buildings, local shops, and cafés.
  • A. Chausseestraße
    Chausseestraße is a major historic street in Berlin, Germany, known for its cultural landmarks and central location.
  • 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. Scharnweberstraße
    Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • D. Paradestraße
    Paradestraße is a Berlin U-Bahn station on the north–south route in the Tempelhof-Schöneberg district, known for serving the U6 line.
  • 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_69aed936de1c81908f91bed80f70abb2 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeebcc8a0481909c35161336bdfbf9 completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d03dbd348190aaaa58a352982248 completed March 14, 2026, 9:16 p.m.
NEDg Description generation batch_69b5d0e2a6948190999ce89edfd3922c completed March 14, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_69b5d11b84ac8190a19015567d4c135a completed March 14, 2026, 9:20 p.m.
Created at: March 9, 2026, 3:19 p.m.