Triple

T15250833
Position Surface form Disambiguated ID Type / Status
Subject Děčínský Sněžník E364513 entity
Predicate partOf P40 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: [Děčínský Sněžník, partOf, Sudetes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sudetes
Context triple: [Děčínský Sněžník, partOf, 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. Balta
    Balta is a city that gained historical significance as a strategic location captured during the Uman–Botoșani offensive in World War II.
  • C. 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.
  • D. Vianen
    Vianen is a historic Dutch town known for its medieval city center and location near major rivers in the western Netherlands.
  • E. Saldus
    Saldus is a small town in western Latvia known for its regional cultural life and as a local economic and administrative center.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f728648190b2c86e4528542b65 completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fee5f390bc8190bc0180c118e1523c completed May 9, 2026, 7:44 a.m.
Created at: April 10, 2026, 3:13 a.m.