Triple

T9826818
Position Surface form Disambiguated ID Type / Status
Subject Schneeberg E238676 entity
Predicate hasSummit P8024 FINISHED
Object Kaiserstein
Kaiserstein is a notable summit point on Austria’s Schneeberg massif, popular with hikers for its alpine views.
E822975 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: Kaiserstein | Statement: [Schneeberg, hasSummit, Kaiserstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaiserstein
Context triple: [Schneeberg, hasSummit, Kaiserstein]
  • A. Ziegelstein
    Ziegelstein is a district in Nuremberg, Germany, known for its residential character and proximity to Nuremberg Airport.
  • B. Plöckenstein
    Plöckenstein is a mountain on the border of Austria, Germany, and the Czech Republic, known as the highest peak of the Bohemian Forest.
  • C. Störnstein
    Störnstein is a small municipality in the Upper Palatinate region of Bavaria, Germany.
  • D. Snekkersten
    Snekkersten is a coastal village in North Zealand, Denmark, known for its seaside location along the Øresund Strait and its proximity to the town of Helsingør.
  • E. Taunusstein
    Taunusstein is a town in the German state of Hesse, located in the scenic Taunus mountain region and known for its residential character and natural surroundings.
  • 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: Kaiserstein
Triple: [Schneeberg, hasSummit, Kaiserstein]
Generated description
Kaiserstein is a notable summit point on Austria’s Schneeberg massif, popular with hikers for its alpine views.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kaiserstein
Target entity description: Kaiserstein is a notable summit point on Austria’s Schneeberg massif, popular with hikers for its alpine views.
  • A. Ziegelstein
    Ziegelstein is a district in Nuremberg, Germany, known for its residential character and proximity to Nuremberg Airport.
  • B. Plöckenstein
    Plöckenstein is a mountain on the border of Austria, Germany, and the Czech Republic, known as the highest peak of the Bohemian Forest.
  • C. Störnstein
    Störnstein is a small municipality in the Upper Palatinate region of Bavaria, Germany.
  • D. Snekkersten
    Snekkersten is a coastal village in North Zealand, Denmark, known for its seaside location along the Øresund Strait and its proximity to the town of Helsingør.
  • E. Taunusstein
    Taunusstein is a town in the German state of Hesse, located in the scenic Taunus mountain region and known for its residential character and natural surroundings.
  • 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_69d1cc88a86c819088f259a049eec4db completed April 5, 2026, 2:44 a.m.
NEDg Description generation batch_69d1cdba64d08190bf0b83d419c4461b completed April 5, 2026, 2:49 a.m.
NED2 Entity disambiguation (via description) batch_69d1ce526a2c819098b103ad83c19445 completed April 5, 2026, 2:52 a.m.
Created at: March 30, 2026, 8:32 p.m.