Triple

T13674192
Position Surface form Disambiguated ID Type / Status
Subject district of Roth E327828 entity
Predicate contains P35 FINISHED
Object Kammerstein
Kammerstein is a municipality in the Roth district of Bavaria, Germany, known for its rural character and proximity to the metropolitan region of Nuremberg.
 E1052745 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: Kammerstein | Statement: [district of Roth, contains, Kammerstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kammerstein
Context triple: [district of Roth, contains, Kammerstein]
  • A. Vestenbergsgreuth
    Vestenbergsgreuth is a small rural municipality in the Bavarian region of Germany, known for its agricultural setting and local Franconian character.
  • B. Schrankogel
    Schrankogel is one of the highest and most prominent mountains in the Stubai Alps of Tyrol, Austria, popular with experienced alpine climbers.
  • C. Gloggnitz
    Gloggnitz is a town in Lower Austria known as a gateway to the Semmering region and an important stop on the historic Southern Railway line.
  • D. Grauspitz
    Grauspitz is a prominent alpine peak in the Rätikon range of the Alps, known as the highest mountain in Liechtenstein and shared with Switzerland.
  • E. Adlkofen
    Adlkofen is a municipality in Lower Bavaria, Germany, situated in the rural region surrounding the city of Landshut.
  • 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: Kammerstein
Triple: [district of Roth, contains, Kammerstein]
Generated description
Kammerstein is a municipality in the Roth district of Bavaria, Germany, known for its rural character and proximity to the metropolitan region of Nuremberg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kammerstein
Target entity description: Kammerstein is a municipality in the Roth district of Bavaria, Germany, known for its rural character and proximity to the metropolitan region of Nuremberg.
  • A. Vestenbergsgreuth
    Vestenbergsgreuth is a small rural municipality in the Bavarian region of Germany, known for its agricultural setting and local Franconian character.
  • B. Schrankogel
    Schrankogel is one of the highest and most prominent mountains in the Stubai Alps of Tyrol, Austria, popular with experienced alpine climbers.
  • C. Gloggnitz
    Gloggnitz is a town in Lower Austria known as a gateway to the Semmering region and an important stop on the historic Southern Railway line.
  • D. Grauspitz
    Grauspitz is a prominent alpine peak in the Rätikon range of the Alps, known as the highest mountain in Liechtenstein and shared with Switzerland.
  • E. Adlkofen
    Adlkofen is a municipality in Lower Bavaria, Germany, situated in the rural region surrounding the city of Landshut.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc65aab348190a6611f5765f8392d completed April 12, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78b145fa081908521c103201f3afe completed May 3, 2026, 5:51 p.m.
NEDg Description generation batch_69f78bd727048190a57a75294a9ab53d completed May 3, 2026, 5:54 p.m.
NED2 Entity disambiguation (via description) batch_69f78c94da6c8190b9bc1d04cee19c3c completed May 3, 2026, 5:57 p.m.
Created at: April 9, 2026, 9:53 p.m.