Triple

T1456309
Position Surface form Disambiguated ID Type / Status
Subject Lower Silesia E31408 entity
Predicate contains P35 FINISHED
Object Głogów E18473 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: Głogów | Statement: [Lower Silesia, contains, Głogów]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Głogów
Context triple: [Lower Silesia, contains, Głogów]
  • A. Glogów chosen
    Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
  • B. Zielona Góra
    Zielona Góra is a city in western Poland known for its wine-making tradition and annual wine festival.
  • C. Kalisz
    Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
  • D. Opole
    Opole is a historic city in southwestern Poland, known as one of the country’s oldest urban centers and a regional cultural hub.
  • E. Wrocław
    Wrocław is a major historic city in southwestern Poland, known for its picturesque Old Town, numerous bridges over the Oder River, and role as a cultural and academic 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_69a49917dfc081909acdbdf5d684f1ef completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c581714881909bf4c2bad9645176 completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f0a6f588190a8a61ab47a858118 completed March 12, 2026, 12:55 a.m.
Created at: March 1, 2026, 8 p.m.