Triple

T3775474
Position Surface form Disambiguated ID Type / Status
Subject Kaisermühlen E83295 entity
Predicate adjacentTo P224 FINISHED
Object Donau City
Donau City is a modern business and residential district in Vienna known for its high-rise buildings and proximity to the Danube River.
 E395330 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: Donau City | Statement: [Kaisermühlen, adjacentTo, Donau City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Donau City
Context triple: [Kaisermühlen, adjacentTo, Donau City]
  • A. Budapest
    Budapest is the capital and largest city of Hungary, renowned for its historic architecture, thermal baths, and prominent location along the Danube River.
  • B. Dunaújváros
    Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
  • C. Győr
    Győr is a historic city in northwestern Hungary, known as an important regional cultural and economic center at the confluence of the Danube, Rába, and Rábca rivers.
  • D. Sopron
    Sopron is a historic city in western Hungary near the Austrian border, known for its well-preserved medieval old town and wine-making traditions.
  • E. Pozsony
    Pozsony is the historical Hungarian name for the city now known as Bratislava, the capital of Slovakia.
  • 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: Donau City
Triple: [Kaisermühlen, adjacentTo, Donau City]
Generated description
Donau City is a modern business and residential district in Vienna known for its high-rise buildings and proximity to the Danube River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Donau City
Target entity description: Donau City is a modern business and residential district in Vienna known for its high-rise buildings and proximity to the Danube River.
  • A. Budapest
    Budapest is the capital and largest city of Hungary, renowned for its historic architecture, thermal baths, and prominent location along the Danube River.
  • B. Dunaújváros
    Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
  • C. Győr
    Győr is a historic city in northwestern Hungary, known as an important regional cultural and economic center at the confluence of the Danube, Rába, and Rábca rivers.
  • D. Sopron
    Sopron is a historic city in western Hungary near the Austrian border, known for its well-preserved medieval old town and wine-making traditions.
  • E. Pozsony
    Pozsony is the historical Hungarian name for the city now known as Bratislava, the capital of Slovakia.
  • 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_69ad8b235e608190b5a2b1d1bfcef50b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc5ac9688190bc921cd3ba1d0580 completed March 8, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51214d77881909a11857a8b8481f9 completed March 14, 2026, 7:45 a.m.
NEDg Description generation batch_69b51318c0348190a665648a19ea8b51 completed March 14, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69b5137d9bb0819085be156826bc945a completed March 14, 2026, 7:51 a.m.
Created at: March 8, 2026, 3:36 p.m.