Triple

T17452967
Position Surface form Disambiguated ID Type / Status
Subject Southwestern Poland E424958 entity
Predicate hasMountainRange P651 FINISHED
Object Sudetes NE NERFINISHED

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: [Southwestern Poland, hasMountainRange, Sudetes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sudetes
Context triple: [Southwestern Poland, hasMountainRange, 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 (2 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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4513faa0c8190961cf504c459bf34 completed April 19, 2026, 3:51 a.m.
Created at: April 10, 2026, 5:47 a.m.