Triple

T3317580
Position Surface form Disambiguated ID Type / Status
Subject Innere Stadt E69717 entity
Predicate borderedBy P224 FINISHED
Object Wieden
Wieden is the 4th municipal district of Vienna, Austria, known for its historic architecture, cultural institutions, and central urban character.
E346711 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: Wieden | Statement: [Innere Stadt, borderedBy, Wieden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wieden
Context triple: [Innere Stadt, borderedBy, Wieden]
  • A. Schwechat
    Schwechat is an Austrian town just southeast of Vienna, best known as the site of Vienna International Airport and a major hub for industry and transport.
  • B. Riehen
    Riehen is a municipality in the canton of Basel-Stadt in northern Switzerland, known as a residential suburb of Basel near the German border.
  • C. Seibersdorf
    Seibersdorf is an Austrian town known for hosting major research and testing laboratories of the International Atomic Energy Agency.
  • D. Wiener Neustadt
    Wiener Neustadt is a historic city in Lower Austria known as a former imperial residence and military stronghold south of Vienna.
  • E. Baden bei Wien
    Baden bei Wien is a historic spa town in eastern Austria renowned for its thermal springs, Biedermeier architecture, and proximity to Vienna.
  • 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: Wieden
Triple: [Innere Stadt, borderedBy, Wieden]
Generated description
Wieden is the 4th municipal district of Vienna, Austria, known for its historic architecture, cultural institutions, and central urban character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wieden
Target entity description: Wieden is the 4th municipal district of Vienna, Austria, known for its historic architecture, cultural institutions, and central urban character.
  • A. Schwechat
    Schwechat is an Austrian town just southeast of Vienna, best known as the site of Vienna International Airport and a major hub for industry and transport.
  • B. Riehen
    Riehen is a municipality in the canton of Basel-Stadt in northern Switzerland, known as a residential suburb of Basel near the German border.
  • C. Seibersdorf
    Seibersdorf is an Austrian town known for hosting major research and testing laboratories of the International Atomic Energy Agency.
  • D. Wiener Neustadt
    Wiener Neustadt is a historic city in Lower Austria known as a former imperial residence and military stronghold south of Vienna.
  • E. Baden bei Wien
    Baden bei Wien is a historic spa town in eastern Austria renowned for its thermal springs, Biedermeier architecture, and proximity to Vienna.
  • 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_69ad85a0bb048190a5458d2738012d61 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb113cb6c8190989b06476f6015fd completed March 8, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3fd5440819092f6847e56c05ff8 completed March 12, 2026, 5:12 p.m.
NEDg Description generation batch_69b300abcbf88190bf05da60d8fb430b completed March 12, 2026, 6:06 p.m.
NED2 Entity disambiguation (via description) batch_69b3132087888190af901e2551ef777c completed March 12, 2026, 7:25 p.m.
Created at: March 8, 2026, 3:11 p.m.