Triple

T18522007
Position Surface form Disambiguated ID Type / Status
Subject Zbigniew Rybczyński E452608 entity
Predicate birthPlace P1 FINISHED
Object Łódź 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: Łódź | Statement: [Zbigniew Rybczyński, birthPlace, Łódź]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Łódź
Context triple: [Zbigniew Rybczyński, birthPlace, Łódź]
  • A. Łódź chosen
    Łódź is one of Poland’s largest cities, historically known as a major industrial and textile manufacturing center.
  • B. Lublin
    Lublin is a historic city in eastern Poland known as a major cultural, academic, and economic center and for its significant role in Polish political history.
  • C. Wrocław
    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.
  • D. Wolsztyn
    Wolsztyn is a town in western Poland known for its historic steam locomotive depot and annual steam engine parade.
  • E. Kalisz
    Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
  • 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_69d8d386df84819092355ebb260d848e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5338e6e188190a41a4ee12c1ad330 completed April 19, 2026, 7:57 p.m.
Created at: April 10, 2026, 11:37 a.m.