Triple

T2628494
Position Surface form Disambiguated ID Type / Status
Subject Lwów Voivodeship E59176 entity
Predicate majorCity P316 FINISHED
Object Rzeszów E220683 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: Rzeszów | Statement: [Lwów Voivodeship, majorCity, Rzeszów]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rzeszów
Context triple: [Lwów Voivodeship, majorCity, Rzeszów]
  • A. Rzeszów chosen
    Rzeszów is a major city in southeastern Poland known as an important economic, academic, and cultural center of the region.
  • B. Przemyśl
    Przemyśl is a historic city in southeastern Poland near the Ukrainian border, known for its strategic location, multicultural heritage, and well-preserved fortifications.
  • C. Tarnów
    Tarnów is a historic city in southern Poland known for its well-preserved Old Town, Renaissance architecture, and cultural heritage.
  • D. Bielsko-Biała
    Bielsko-Biała is a city in southern Poland at the foot of the Beskid Mountains, known as a regional industrial and cultural center formed from the historic towns of Bielsko and Biała.
  • E. Kielce
    Kielce is a city in south-central Poland known as an important regional center for industry, education, and culture.
  • 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_69ab4ac558388190962492cd2e1b0ce6 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8c2e3d88190a972f58356f282cc completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5f57163e08190934045ea34486605 completed March 14, 2026, 11:55 p.m.
Created at: March 6, 2026, 9:50 p.m.