Triple

T16407933
Position Surface form Disambiguated ID Type / Status
Subject Bad Nauheim E398483 entity
Predicate hasLandmark P105 FINISHED
Object Sprudelhof
Sprudelhof is a historic Art Nouveau spa complex in Bad Nauheim, Germany, renowned for its ornate bathhouses and central fountain courtyards.
E1212346 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: Sprudelhof | Statement: [Bad Nauheim, hasLandmark, Sprudelhof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sprudelhof
Context triple: [Bad Nauheim, hasLandmark, Sprudelhof]
  • A. Saalhof
    Saalhof is a historic medieval building complex in Frankfurt am Main that forms part of the city’s museum landscape and reflects its architectural and urban history.
  • B. Heiderhof
    Heiderhof is a residential subdistrict of the Bonn borough Bad Godesberg in western Germany.
  • C. Porschdorf
    Porschdorf is a village in Saxony, Germany, that forms part of the spa town and municipality of Bad Schandau in the Saxon Switzerland region.
  • D. Pfaffenstein
    Pfaffenstein is a prominent table mountain in Germany’s Elbe Sandstone Mountains, known for its striking rock formations and popular hiking routes.
  • E. Kubschütz
    Kubschütz is a small municipality in the German state of Saxony, located near the town of Bautzen and known for its rural character and Sorbian cultural heritage.
  • 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: Sprudelhof
Triple: [Bad Nauheim, hasLandmark, Sprudelhof]
Generated description
Sprudelhof is a historic Art Nouveau spa complex in Bad Nauheim, Germany, renowned for its ornate bathhouses and central fountain courtyards.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sprudelhof
Target entity description: Sprudelhof is a historic Art Nouveau spa complex in Bad Nauheim, Germany, renowned for its ornate bathhouses and central fountain courtyards.
  • A. Saalhof
    Saalhof is a historic medieval building complex in Frankfurt am Main that forms part of the city’s museum landscape and reflects its architectural and urban history.
  • B. Heiderhof
    Heiderhof is a residential subdistrict of the Bonn borough Bad Godesberg in western Germany.
  • C. Porschdorf
    Porschdorf is a village in Saxony, Germany, that forms part of the spa town and municipality of Bad Schandau in the Saxon Switzerland region.
  • D. Pfaffenstein
    Pfaffenstein is a prominent table mountain in Germany’s Elbe Sandstone Mountains, known for its striking rock formations and popular hiking routes.
  • E. Kubschütz
    Kubschütz is a small municipality in the German state of Saxony, located near the town of Bautzen and known for its rural character and Sorbian cultural heritage.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32870e44c8190aae7bc6e6022ceb7 completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c64a05c8190a59e800ce2318052 completed May 10, 2026, 8:05 a.m.
NEDg Description generation batch_6a003dfdd4f88190b86db12bb9c7217a completed May 10, 2026, 8:12 a.m.
NED2 Entity disambiguation (via description) batch_6a003e953ca88190bb7c64c12a46c666 completed May 10, 2026, 8:15 a.m.
Created at: April 10, 2026, 5:09 a.m.