Triple

T15937026
Position Surface form Disambiguated ID Type / Status
Subject Donaustadt E386464 entity
Predicate contains P35 FINISHED
Object Stadlau
Stadlau is a residential and commercial neighborhood in Vienna’s 22nd district, Donaustadt, known for its transport links and mixed urban development.
E1184442 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: Stadlau | Statement: [Donaustadt, contains, Stadlau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stadlau
Context triple: [Donaustadt, contains, Stadlau]
  • A. Günterstal
    Günterstal is a district of Freiburg im Breisgau in southwestern Germany, known for its scenic valley setting in the Black Forest and historic monastery.
  • B. Stauchitz
    Stauchitz is a small municipality in the Free State of Saxony in eastern Germany, known for its rural character and location within the historic Meissen region.
  • C. Lochau
    Lochau is a locality in Germany historically noted as the place where the influential Reformation-era prince Frederick the Wise died.
  • D. Tennstädt
    Tennstädt is a small town in the Thuringia region of central Germany.
  • E. Riederau
    Riederau is a small lakeside district of Dießen am Ammersee in Bavaria, Germany, known for its scenic location on the shores of Lake Ammersee.
  • 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: Stadlau
Triple: [Donaustadt, contains, Stadlau]
Generated description
Stadlau is a residential and commercial neighborhood in Vienna’s 22nd district, Donaustadt, known for its transport links and mixed urban development.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Stadlau
Target entity description: Stadlau is a residential and commercial neighborhood in Vienna’s 22nd district, Donaustadt, known for its transport links and mixed urban development.
  • A. Günterstal
    Günterstal is a district of Freiburg im Breisgau in southwestern Germany, known for its scenic valley setting in the Black Forest and historic monastery.
  • B. Stauchitz
    Stauchitz is a small municipality in the Free State of Saxony in eastern Germany, known for its rural character and location within the historic Meissen region.
  • C. Lochau
    Lochau is a locality in Germany historically noted as the place where the influential Reformation-era prince Frederick the Wise died.
  • D. Tennstädt
    Tennstädt is a small town in the Thuringia region of central Germany.
  • E. Riederau
    Riederau is a small lakeside district of Dießen am Ammersee in Bavaria, Germany, known for its scenic location on the shores of Lake Ammersee.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156ab7f548190b2d1aafa0e6d2c24 completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5b8121881909b15bf6451d3d3a8 completed May 9, 2026, 10:31 p.m.
NEDg Description generation batch_69ffb718d60481908ac0034ed8d8abc5 completed May 9, 2026, 10:37 p.m.
NED2 Entity disambiguation (via description) batch_69ffb7c98cf8819097c7012040dbfe89 completed May 9, 2026, 10:40 p.m.
Created at: April 10, 2026, 4:53 a.m.