Triple

T4358296
Position Surface form Disambiguated ID Type / Status
Subject Variscan orogeny E98603 entity
Predicate affects P9 FINISHED
Object Sudetes E49632 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: Sudetes | Statement: [Variscan orogeny, affects, Sudetes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sudetes
Context triple: [Variscan orogeny, affects, Sudetes]
  • A. Sudetes chosen
    The Sudetes are a mountain range in Central Europe spanning parts of Poland, the Czech Republic, and Germany, known for their forested peaks, mineral resources, and popular spa and ski resorts.
  • B. Aukštaitija
    Aukštaitija is a historical and ethnographic region in northeastern Lithuania known for its lakes, forests, and strong preservation of traditional Lithuanian culture and dialects.
  • C. Vianen
    Vianen is a historic Dutch town known for its medieval city center and location near major rivers in the western Netherlands.
  • D. Samogitia
    Samogitia is a historic ethnographic region in northwestern Lithuania known for its distinct Samogitian dialect, strong cultural identity, and late Christianization compared to the rest of Europe.
  • E. Sudetes mountains
    The Sudetes mountains are a mountain range in Central Europe stretching along the border of Poland, the Czech Republic, and Germany, known for their varied landscapes and historical significance.
  • 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_69b3454c772081908e20173e379e8ebe completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351c7fa1881908bdc844a7142eb65 completed March 12, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5dbbcb6188190a8a4da6a080f0d61 completed March 14, 2026, 10:05 p.m.
Created at: March 12, 2026, 11:16 p.m.