Triple

T13084809
Position Surface form Disambiguated ID Type / Status
Subject Hornbergs strand E310302 entity
Predicate hasNameElement P3097 FINISHED
Object Hornberg E509535 NE FINISHED

How this triple was built (2 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: Hornberg | Statement: [Hornbergs strand, hasNameElement, Hornberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hornberg
Context triple: [Hornbergs strand, hasNameElement, Hornberg]
  • A. Hornberg chosen
    Hornberg is a small town in the Black Forest region of Baden-Württemberg, Germany, known for its scenic landscape and traditional cuckoo clock craftsmanship.
  • B. Hornsberg
    Hornsberg is a waterfront residential and commercial district on the island of Kungsholmen in central Stockholm, Sweden.
  • C. 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.
  • D. Hasliberg
    Hasliberg is a Swiss alpine village and municipality in the canton of Bern, known for its mountain scenery and ski and hiking resort facilities.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d806a733548190989cfd4ce981ca33 completed April 9, 2026, 8:05 p.m.
NER Named-entity recognition batch_69d981361e8c819099376435aa3a7aa3 completed April 10, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff051bc88190a55c55377a352d3b completed May 3, 2026, 7:53 a.m.
Created at: April 9, 2026, 9:02 p.m.