Triple

T1161940
Position Surface form Disambiguated ID Type / Status
Subject Bochnia E24511 entity
Predicate hasRailConnectionTo P848 FINISHED
Object Tarnów E23368 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: Tarnów | Statement: [Bochnia, hasRailConnectionTo, Tarnów]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tarnów
Context triple: [Bochnia, hasRailConnectionTo, Tarnów]
  • A. Tarnów chosen
    Tarnów is a historic city in southern Poland known for its well-preserved Old Town, Renaissance architecture, and cultural heritage.
  • 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. Kielce
    Kielce is a city in south-central Poland known as an important regional center for industry, education, and culture.
  • D. Kalisz
    Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
  • E. 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.
  • 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_69a494060e148190abb42f971242c197 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bcb1915081908834ced85d09e299 completed March 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae891551c8819090f6edd70c45ff39 completed March 9, 2026, 8:47 a.m.
Created at: March 1, 2026, 7:45 p.m.