Triple

T2804595
Position Surface form Disambiguated ID Type / Status
Subject Silesia E54020 entity
Predicate containsMountainRange P651 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: [Silesia, containsMountainRange, Sudetes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sudetes
Context triple: [Silesia, containsMountainRange, 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. Baltiysk
    Baltiysk is a Russian port town in the Kaliningrad Oblast, strategically located on the Baltic Sea and serving as an important naval base.
  • 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_69ab49dcee188190b5c6eca9ae9e3469 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde1525888190b3c04e10043c67d6 completed March 7, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc674217c81908177b088cc824e7b completed March 10, 2026, 7:21 a.m.
Created at: March 6, 2026, 9:59 p.m.