Triple

T3449051
Position Surface form Disambiguated ID Type / Status
Subject Reinickendorfer Straße E72747 entity
Predicate hasEntranceFrom P1985 FINISHED
Object Gerichtstraße
Gerichtstraße is a street in Berlin, Germany, located in the Wedding district and known for its mix of residential buildings, commercial spaces, and cultural venues.
 E406003 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: Gerichtstraße | Statement: [Reinickendorfer Straße, hasEntranceFrom, Gerichtstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gerichtstraße
Context triple: [Reinickendorfer Straße, hasEntranceFrom, Gerichtstraße]
  • A. Kaufingerstraße
    Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
  • B. Paradestraße
    Paradestraße is a Berlin U-Bahn station on the north–south route in the Tempelhof-Schöneberg district, known for serving the U6 line.
  • C. Chausseestraße
    Chausseestraße is a major historic street in Berlin, Germany, known for its cultural landmarks and central location.
  • D. Schulstraße
    Schulstraße is a nearby street in the vicinity of Leopoldplatz in Berlin, Germany.
  • E. Herbertstraße
    Herbertstraße is a short, gated street in Hamburg’s St. Pauli district known as one of Germany’s most famous red-light prostitution streets.
  • 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: Gerichtstraße
Triple: [Reinickendorfer Straße, hasEntranceFrom, Gerichtstraße]
Generated description
Gerichtstraße is a street in Berlin, Germany, located in the Wedding district and known for its mix of residential buildings, commercial spaces, and cultural venues.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gerichtstraße
Target entity description: Gerichtstraße is a street in Berlin, Germany, located in the Wedding district and known for its mix of residential buildings, commercial spaces, and cultural venues.
  • A. Kaufingerstraße
    Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
  • B. Paradestraße
    Paradestraße is a Berlin U-Bahn station on the north–south route in the Tempelhof-Schöneberg district, known for serving the U6 line.
  • C. Chausseestraße
    Chausseestraße is a major historic street in Berlin, Germany, known for its cultural landmarks and central location.
  • D. Schulstraße
    Schulstraße is a nearby street in the vicinity of Leopoldplatz in Berlin, Germany.
  • E. Herbertstraße
    Herbertstraße is a short, gated street in Hamburg’s St. Pauli district known as one of Germany’s most famous red-light prostitution streets.
  • 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_69ad85b05c848190b7a28ceec2bd7b74 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adba71f4a4819089d08b871cc9b16f completed March 8, 2026, 6:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c2144708190a4a620222eeee5d3 completed March 14, 2026, 11:53 a.m.
NEDg Description generation batch_69b54da520b481909ee2a47943a07045 completed March 14, 2026, 11:59 a.m.
NED2 Entity disambiguation (via description) batch_69b54e16cde48190bb82f0eb04470629 completed March 14, 2026, 12:01 p.m.
Created at: March 8, 2026, 3:16 p.m.