Triple

T4604195
Position Surface form Disambiguated ID Type / Status
Subject Vosges department E100389 entity
Predicate highestPoint P210 FINISHED
Object Hohneck E249460 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: Hohneck | Statement: [Vosges department, highestPoint, Hohneck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hohneck
Context triple: [Vosges department, highestPoint, Hohneck]
  • A. Hohneck chosen
    Hohneck is one of the highest peaks in the Vosges Mountains of northeastern France, known for its panoramic views and popular hiking and skiing opportunities.
  • B. Hornsberg
    Hornsberg is a waterfront residential and commercial district on the island of Kungsholmen in central Stockholm, Sweden.
  • C. Kölzig
    Kölzig is the surname of former professional ice hockey goaltender Olie Kolzig, best known for his long NHL career with the Washington Capitals.
  • D. Braubach
    Braubach is a historic town on the Rhine River in Germany, best known for its well-preserved medieval architecture and the prominent Marksburg Castle overlooking it.
  • E. Neefe
    Neefe is a German surname most notably associated with Christian Gottlob Neefe, an 18th-century composer and one of Beethoven’s early teachers.
  • 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_69bd43cce1e08190a07d53af6a9b6c24 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5999f9c88190a43309573df61159 completed March 20, 2026, 2:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69be438d66088190b062c8bf4ceba653 completed March 21, 2026, 7:06 a.m.
Created at: March 20, 2026, 1:12 p.m.