Triple

T18025461
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Pure and Applied Mathematics E431235 entity
Predicate city P40 FINISHED
Object Wrocław 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: Wrocław | Statement: [Faculty of Pure and Applied Mathematics, city, Wrocław]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wrocław
Context triple: [Faculty of Pure and Applied Mathematics, city, 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. Wolsztyn
    Wolsztyn is a town in western Poland known for its historic steam locomotive depot and annual steam engine parade.
  • 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_69d8b9050fb48190890155145deb0a66 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4b9c554348190bd0df06d0cfe188e completed April 19, 2026, 11:17 a.m.
Created at: April 10, 2026, 10:24 a.m.