Triple

T13230867
Position Surface form Disambiguated ID Type / Status
Subject Bolesławiec E315012 entity
Predicate hasNearbyCity P350 FINISHED
Object Legnica 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: Legnica | Statement: [Bolesławiec, hasNearbyCity, Legnica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Legnica
Context triple: [Bolesławiec, hasNearbyCity, Legnica]
  • A. Legnica chosen
    Legnica is a historic city in southwestern Poland known for its medieval architecture, including a prominent castle and old town, and its role as a regional cultural and economic center.
  • B. Kluczbork
    Kluczbork is a town in southern Poland known as a local administrative, cultural, and economic center in the Opole region.
  • C. Olsztynek
    Olsztynek is a small historic town in northern Poland known for its open-air ethnographic museum and location within the picturesque Warmian-Masurian lake district.
  • D. Bolesławiec
    Bolesławiec is a historic town in southwestern Poland renowned for its traditional hand-decorated pottery.
  • E. Glogów
    Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d336ae08190bfc118cfbefddf84 completed April 10, 2026, 11:52 p.m.
Created at: April 9, 2026, 9:22 p.m.