Triple

T3512094
Position Surface form Disambiguated ID Type / Status
Subject Lutynia, Poland E74218 entity
Predicate hasNearbyCity P350 FINISHED
Object Wrocław E17157 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: Wrocław | Statement: [Lutynia, Poland, hasNearbyCity, Wrocław]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wrocław
Context triple: [Lutynia, Poland, hasNearbyCity, Wrocław]
  • A. Wrocław chosen
    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.
  • B. Katowice
    Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
  • C. Poznań
    Poznań is a historic and economically significant city in western Poland, known for its medieval Old Town, role as an early center of Polish statehood, and status as a major academic and industrial hub.
  • D. Kraków
    Kraków is one of Poland’s oldest and most historically significant cities, renowned for its well-preserved medieval core, royal heritage, and cultural institutions.
  • E. Opole Silesia
    Opole Silesia is a historical and cultural region in southwestern Poland, known for its mixed Polish-German heritage and centered around the city of Opole.
  • 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_69ad85cfb5c881909c9a2edd9d6043cc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc10b6b48190bedfed6d34afc425 completed March 8, 2026, 6:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfa91dde508190abd38b4cf132ad5e completed March 22, 2026, 8:32 a.m.
Created at: March 8, 2026, 3:19 p.m.