Triple

T9826858
Position Surface form Disambiguated ID Type / Status
Subject Krems an der Donau E238677 entity
Predicate hasPart P35 FINISHED
Object Gneixendorf
Gneixendorf is a village and cadastral community that forms part of the city of Krems an der Donau in Lower Austria.
E889391 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: Gneixendorf | Statement: [Krems an der Donau, hasPart, Gneixendorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gneixendorf
Context triple: [Krems an der Donau, hasPart, Gneixendorf]
  • A. Pottendorf
    Pottendorf is a market town in Lower Austria known for its historic castle and location within the Baden district.
  • B. Adendorf
    Adendorf is a village-sized district within the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • C. Kiliansdorf
    Kiliansdorf is a village and district of the town of Roth in the Bavarian region of Germany.
  • D. Eugendorf
    Eugendorf is a market town in the Austrian state of Salzburg, known for its proximity to the city of Salzburg and its location in the scenic Salzkammergut region.
  • E. Ebreichsdorf
    Ebreichsdorf is a small town in Lower Austria known for its equestrian facilities 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: Gneixendorf
Triple: [Krems an der Donau, hasPart, Gneixendorf]
Generated description
Gneixendorf is a village and cadastral community that forms part of the city of Krems an der Donau in Lower Austria.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gneixendorf
Target entity description: Gneixendorf is a village and cadastral community that forms part of the city of Krems an der Donau in Lower Austria.
  • A. Pottendorf
    Pottendorf is a market town in Lower Austria known for its historic castle and location within the Baden district.
  • B. Adendorf
    Adendorf is a village-sized district within the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • C. Kiliansdorf
    Kiliansdorf is a village and district of the town of Roth in the Bavarian region of Germany.
  • D. Eugendorf
    Eugendorf is a market town in the Austrian state of Salzburg, known for its proximity to the city of Salzburg and its location in the scenic Salzkammergut region.
  • E. Ebreichsdorf
    Ebreichsdorf is a small town in Lower Austria known for its equestrian facilities 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_69ca84e0dd1881909800765d1e21f735 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb324e7848190b9424a78ca653afe completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69deafff4b8c819099d47b48773c3629 completed April 14, 2026, 9:22 p.m.
NEDg Description generation batch_69dec2534728819095b3693120772da9 completed April 14, 2026, 10:40 p.m.
NED2 Entity disambiguation (via description) batch_69dec79b1b548190a74312284f98551c completed April 14, 2026, 11:02 p.m.
Created at: March 30, 2026, 8:32 p.m.