Triple

T4244949
Position Surface form Disambiguated ID Type / Status
Subject Union of Polish Metropolises E95505 entity
Predicate hasMember P10 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: [Union of Polish Metropolises, hasMember, Rzeszów]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rzeszów
Context triple: [Union of Polish Metropolises, hasMember, 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_69b3453d91548190b4d4ef8fe52aa2ac completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e8c42e88190b309a1ef7f6529ac completed March 12, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b6509a86a081908435094d0e80e9f4 completed March 15, 2026, 6:24 a.m.
Created at: March 12, 2026, 11:05 p.m.