Triple

T7419902
Position Surface form Disambiguated ID Type / Status
Subject Hahnenklee E171218 entity
Predicate near P350 FINISHED
Object Bocksberg
Bocksberg is a mountain in the Harz region of Germany, known for its hiking trails, winter sports facilities, and scenic views near the village of Hahnenklee.
E662755 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: Bocksberg | Statement: [Hahnenklee, near, Bocksberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bocksberg
Context triple: [Hahnenklee, near, Bocksberg]
  • A. Hangelsberg
    Hangelsberg is a village in the German state of Brandenburg, known as a district of the municipality Grünheide (Mark) in the Oder-Spree region.
  • B. Schlossberg
    Schlossberg is a historic hill in Graz, Austria, known for its fortress ruins, iconic clock tower, and panoramic views over the city.
  • C. Hornberg
    Hornberg is a small town in the Black Forest region of Baden-Württemberg, Germany, known for its scenic landscape and traditional cuckoo clock craftsmanship.
  • D. Festungsberg
    Festungsberg is a prominent hill in Salzburg, Austria, best known as the site of the medieval Hohensalzburg Fortress overlooking the city.
  • E. Ziegenberg
    Ziegenberg is a locality in Hesse, Germany, historically notable for its role and nearby military installations during the later years of World War II.
  • 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: Bocksberg
Triple: [Hahnenklee, near, Bocksberg]
Generated description
Bocksberg is a mountain in the Harz region of Germany, known for its hiking trails, winter sports facilities, and scenic views near the village of Hahnenklee.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bocksberg
Target entity description: Bocksberg is a mountain in the Harz region of Germany, known for its hiking trails, winter sports facilities, and scenic views near the village of Hahnenklee.
  • A. Hangelsberg
    Hangelsberg is a village in the German state of Brandenburg, known as a district of the municipality Grünheide (Mark) in the Oder-Spree region.
  • B. Schlossberg
    Schlossberg is a historic hill in Graz, Austria, known for its fortress ruins, iconic clock tower, and panoramic views over the city.
  • C. Hornberg
    Hornberg is a small town in the Black Forest region of Baden-Württemberg, Germany, known for its scenic landscape and traditional cuckoo clock craftsmanship.
  • D. Festungsberg
    Festungsberg is a prominent hill in Salzburg, Austria, best known as the site of the medieval Hohensalzburg Fortress overlooking the city.
  • E. Ziegenberg
    Ziegenberg is a locality in Hesse, Germany, historically notable for its role and nearby military installations during the later years of World War II.
  • 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_69c68a625d048190af70eb8b63bec5a0 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f2ea61248190886e8e55b42ba5f1 completed March 27, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81ef7fc808190a564ab4d9d97ab37 completed March 28, 2026, 6:33 p.m.
NEDg Description generation batch_69c81f9b565881909bebcc3112037f52 completed March 28, 2026, 6:36 p.m.
NED2 Entity disambiguation (via description) batch_69c8207912f4819086e99ed441bee805 completed March 28, 2026, 6:39 p.m.
Created at: March 27, 2026, 3:11 p.m.