Triple

T1547869
Position Surface form Disambiguated ID Type / Status
Subject Greater Poland E33019 entity
Predicate historicalCapital P2536 FINISHED
Object Gniezno E226276 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: Gniezno | Statement: [Greater Poland, historicalCapital, Gniezno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gniezno
Context triple: [Greater Poland, historicalCapital, Gniezno]
  • A. Gniezno chosen
    Gniezno is a historic city in west-central Poland, renowned as the country’s first capital and an early center of Polish statehood and Christianity.
  • B. Toruń
    Toruń is a historic city in northern Poland, renowned for its well-preserved medieval Old Town and as the birthplace of astronomer Nicolaus Copernicus.
  • C. Sandomierz
    Sandomierz is a historic town in southeastern Poland, known for its well-preserved Old Town, medieval architecture, and picturesque location on the Vistula River.
  • D. Zamość
    Zamość is a Renaissance-planned city in southeastern Poland, renowned for its well-preserved Old Town and UNESCO World Heritage status.
  • E. 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.
  • 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_69a885ee6db8819099502bc5ce8af881 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb20dd5a88190b3d6e6f0004fe9b4 completed March 7, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fb455888190a1408a25b93a70ce completed March 9, 2026, 1:17 a.m.
Created at: March 4, 2026, 7:26 p.m.