Triple

T11646564
Position Surface form Disambiguated ID Type / Status
Subject Leopoldstadt E276789 entity
Predicate borderedBy P224 FINISHED
Object Donaustadt E386464 NE FINISHED

How this triple was built (2 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: Donaustadt | Statement: [Leopoldstadt, borderedBy, Donaustadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Donaustadt
Context triple: [Leopoldstadt, borderedBy, Donaustadt]
  • A. Donaustadt chosen
    Donaustadt is the 22nd district of Vienna, Austria, known for its extensive residential areas, modern developments, and the location of the Vienna International Centre.
  • B. Döbling
    Döbling is a residential district in the northwest of Vienna, Austria, known for its vineyards, green hills, and affluent neighborhoods.
  • C. Ottakring
    Ottakring is a diverse, traditionally working-class district in western Vienna known for its multicultural atmosphere, historic brewery, and vibrant urban life.
  • D. 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.
  • E. Mödling
    Mödling is a historic town in Lower Austria, near Vienna, known for its picturesque old town, wine culture, and proximity to the Vienna Woods.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aafbb3c081908a9cdb4ecb8d981d completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a2cc8bfc8190a063cc37de9596a9 completed April 10, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef1381a49c81909d849edbfab7448e completed April 27, 2026, 7:42 a.m.
Created at: April 8, 2026, 9:39 p.m.