Triple

T19489332
Position Surface form Disambiguated ID Type / Status
Subject Kutno County E487604 entity
Predicate hasUrbanGmina P46875 FINISHED
Object Żychlin 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: Żychlin | Statement: [Kutno County, hasUrbanGmina, Żychlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Żychlin
Context triple: [Kutno County, hasUrbanGmina, Żychlin]
  • A. Żychlin chosen
    Żychlin is a small town in central Poland known for its historical Jewish community and location within the Łódź Voivodeship.
  • B. Tarnopol
    Tarnopol is a historic city in western Ukraine, now known as Ternopil, which has long served as a regional cultural and administrative center.
  • C. Czerniaków
    Czerniaków is a Polish surname most notably borne by Adam Czerniaków, the head of the Warsaw Ghetto Jewish Council during World War II.
  • D. Czerniaków
    Czerniaków is a historic neighborhood in Warsaw, Poland, situated along the Vistula River and known for its prewar architecture and role in the city’s wartime history.
  • E. Lemberg
    Lemberg is a prominent mountain in the Swabian Jura of Baden-Württemberg, Germany, known as the highest peak in that range.
  • 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_69d8e8d924388190b847cb15bb3d0aff completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6348ad4088190b530f47efca90165 completed April 20, 2026, 2:13 p.m.
Created at: April 10, 2026, 1:39 p.m.