Triple

T3390444
Position Surface form Disambiguated ID Type / Status
Subject Leopoldplatz E71403 entity
Predicate hasNearbyStreet P8235 FINISHED
Object Schulstraße
Schulstraße is a nearby street in the vicinity of Leopoldplatz in Berlin, Germany.
 E381466 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: Schulstraße | Statement: [Leopoldplatz, hasNearbyStreet, Schulstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Schulstraße
Context triple: [Leopoldplatz, hasNearbyStreet, Schulstraße]
  • A. Müllerstraße
    Müllerstraße is a major thoroughfare in Berlin’s Wedding district, known for its dense urban character, shops, and public transport connections.
  • B. Scharnweberstraße
    Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • C. Schwartzkopffstraße
    Schwartzkopffstraße is a Berlin U-Bahn station on the U6 line located in the central district of the city.
  • D. Leipziger Straße
    Leipziger Straße is a major historic thoroughfare in central Berlin, known for its government buildings, commercial centers, and role in the city’s urban core.
  • E. Kaufingerstraße
    Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
  • 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: Schulstraße
Triple: [Leopoldplatz, hasNearbyStreet, Schulstraße]
Generated description
Schulstraße is a nearby street in the vicinity of Leopoldplatz in Berlin, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Schulstraße
Target entity description: Schulstraße is a nearby street in the vicinity of Leopoldplatz in Berlin, Germany.
  • A. Müllerstraße
    Müllerstraße is a major thoroughfare in Berlin’s Wedding district, known for its dense urban character, shops, and public transport connections.
  • B. Scharnweberstraße
    Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • C. Schwartzkopffstraße
    Schwartzkopffstraße is a Berlin U-Bahn station on the U6 line located in the central district of the city.
  • D. Leipziger Straße
    Leipziger Straße is a major historic thoroughfare in central Berlin, known for its government buildings, commercial centers, and role in the city’s urban core.
  • E. Kaufingerstraße
    Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
  • 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_69b4cdc9089481909e9ef5f5e7edeaa6 completed March 14, 2026, 2:54 a.m.
NEDg Description generation batch_69b4cf5535748190b5dc3f23d1692e51 completed March 14, 2026, 3 a.m.
NED2 Entity disambiguation (via description) batch_69b4cfc29a18819087935c16f6ecd9e4 completed March 14, 2026, 3:02 a.m.
Created at: March 8, 2026, 3:14 p.m.