Triple

T4314307
Position Surface form Disambiguated ID Type / Status
Subject Rhön E94149 entity
Predicate near P350 FINISHED
Object Vogelsberg
Vogelsberg is a large volcanic mountain range in the German state of Hesse, known for its forested highlands and rural landscapes.
E435823 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: Vogelsberg | Statement: [Rhön, near, Vogelsberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vogelsberg
Context triple: [Rhön, near, Vogelsberg]
  • A. Todtnau
    Todtnau is a small town in Germany’s Black Forest region, known for its mountainous scenery, outdoor recreation, and proximity to the Feldberg peak.
  • B. Ettersberg
    Ettersberg is a hill and surrounding area near Weimar in Thuringia, Germany, historically known as the site of the Buchenwald concentration camp.
  • C. Schneeberg
    Schneeberg is a prominent alpine mountain in eastern Austria, known as the easternmost two-thousander of the Alps and a popular destination for hiking and skiing.
  • D. Paterberg
    Paterberg is a short but brutally steep cobbled hill in the Flemish Ardennes, famous as a decisive climb in professional cycling races.
  • E. Limpertsberg
    Limpertsberg is an affluent residential and educational district of Luxembourg City known for its elegant townhouses, schools, and proximity to the city center.
  • 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: Vogelsberg
Triple: [Rhön, near, Vogelsberg]
Generated description
Vogelsberg is a large volcanic mountain range in the German state of Hesse, known for its forested highlands and rural landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vogelsberg
Target entity description: Vogelsberg is a large volcanic mountain range in the German state of Hesse, known for its forested highlands and rural landscapes.
  • A. Todtnau
    Todtnau is a small town in Germany’s Black Forest region, known for its mountainous scenery, outdoor recreation, and proximity to the Feldberg peak.
  • B. Ettersberg
    Ettersberg is a hill and surrounding area near Weimar in Thuringia, Germany, historically known as the site of the Buchenwald concentration camp.
  • C. Schneeberg
    Schneeberg is a prominent alpine mountain in eastern Austria, known as the easternmost two-thousander of the Alps and a popular destination for hiking and skiing.
  • D. Paterberg
    Paterberg is a short but brutally steep cobbled hill in the Flemish Ardennes, famous as a decisive climb in professional cycling races.
  • E. Limpertsberg
    Limpertsberg is an affluent residential and educational district of Luxembourg City known for its elegant townhouses, schools, and proximity to the city center.
  • 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_69b3451886588190a3dd1305ea7c58dc completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b350f4448481908be2c7df9cc71bb9 completed March 12, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e4ef0ca881908d9811183adc26c4 completed March 14, 2026, 10:45 p.m.
NEDg Description generation batch_69b5e5b3ba208190b6cb5e40f9e744e8 completed March 14, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_69b5e62af694819086b3eddb71f591d2 completed March 14, 2026, 10:50 p.m.
Created at: March 12, 2026, 11:12 p.m.