Triple

T13754652
Position Surface form Disambiguated ID Type / Status
Subject Donau-Ries E330443 entity
Predicate containsMunicipality P852 FINISHED
Object Fünfstetten
Fünfstetten is a small rural municipality in the Donau-Ries district of Bavaria in southern Germany.
E1060514 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: Fünfstetten | Statement: [Donau-Ries, containsMunicipality, Fünfstetten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fünfstetten
Context triple: [Donau-Ries, containsMunicipality, Fünfstetten]
  • A. Hohe Acht
    Hohe Acht is the highest peak in Germany’s Eifel region, known for its volcanic origins and panoramic views.
  • B. Bad Grönenbach
    Bad Grönenbach is a spa town in the Bavarian Allgäu region of southern Germany, known for its health resorts and picturesque rural surroundings.
  • C. Furth im Wald
    Furth im Wald is a small Bavarian town in southeastern Germany, known for its traditional Drachenstich (dragon-slaying) festival and picturesque setting near the Czech border.
  • D. Bad Lippspringe
    Bad Lippspringe is a spa town in North Rhine-Westphalia, Germany, known for its therapeutic springs and health resorts.
  • E. Schaufling
    Schaufling is a small municipality in the Bavarian district of Regen in southeastern Germany, known for its rural setting in the Bavarian Forest region.
  • 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: Fünfstetten
Triple: [Donau-Ries, containsMunicipality, Fünfstetten]
Generated description
Fünfstetten is a small rural municipality in the Donau-Ries district of Bavaria in southern Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Fünfstetten
Target entity description: Fünfstetten is a small rural municipality in the Donau-Ries district of Bavaria in southern Germany.
  • A. Hohe Acht
    Hohe Acht is the highest peak in Germany’s Eifel region, known for its volcanic origins and panoramic views.
  • B. Bad Grönenbach
    Bad Grönenbach is a spa town in the Bavarian Allgäu region of southern Germany, known for its health resorts and picturesque rural surroundings.
  • C. Furth im Wald
    Furth im Wald is a small Bavarian town in southeastern Germany, known for its traditional Drachenstich (dragon-slaying) festival and picturesque setting near the Czech border.
  • D. Bad Lippspringe
    Bad Lippspringe is a spa town in North Rhine-Westphalia, Germany, known for its therapeutic springs and health resorts.
  • E. Schaufling
    Schaufling is a small municipality in the Bavarian district of Regen in southeastern Germany, known for its rural setting in the Bavarian Forest region.
  • 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02179c948190a652cc8c586e418f completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7a859e6748190aa1899830a02b710 completed May 3, 2026, 7:56 p.m.
NEDg Description generation batch_69f7a91deb3c8190ad2be7f1ca99ac9b completed May 3, 2026, 7:59 p.m.
NED2 Entity disambiguation (via description) batch_69f7ad51c6808190afa80fc3622399bf completed May 3, 2026, 8:17 p.m.
Created at: April 9, 2026, 10:09 p.m.