Triple

T1029792
Position Surface form Disambiguated ID Type / Status
Subject Świętokrzyskie Voivodeship E22223 entity
Predicate seatOfGovernment P761 FINISHED
Object Kielce E194016 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: Kielce | Statement: [Świętokrzyskie Voivodeship, seatOfGovernment, Kielce]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kielce
Context triple: [Świętokrzyskie Voivodeship, seatOfGovernment, Kielce]
  • A. Kielce chosen
    Kielce is a city in south-central Poland known as an important regional center for industry, education, and culture.
  • B. Kalisz
    Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
  • C. Tarnów
    Tarnów is a historic city in southern Poland known for its well-preserved Old Town, Renaissance architecture, and cultural heritage.
  • D. 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.
  • E. 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.
  • 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7f962608190b3ebd9140472b979 completed March 1, 2026, 10:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ada0b24844819090904b831c73495c completed March 8, 2026, 4:15 p.m.
Created at: March 1, 2026, 7:41 p.m.