Triple

T6013189
Position Surface form Disambiguated ID Type / Status
Subject Kalisz E133882 entity
Predicate hasTwinTown P919 FINISHED
Object Prešov E83895 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: Prešov | Statement: [Kalisz, hasTwinTown, Prešov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prešov
Context triple: [Kalisz, hasTwinTown, Prešov]
  • A. Prešov chosen
    Prešov is a historic city in eastern Slovakia known for its preserved medieval center and role as a regional cultural and economic hub.
  • B. Banská Bystrica
    Banská Bystrica is a historic central Slovak city best known as the main center of the anti-Nazi Slovak National Uprising during World War II.
  • C. Trnava
    Trnava is a historic city in western Slovakia known for its well-preserved medieval center and numerous churches, earning it the nickname "Little Rome."
  • D. Považská Bystrica
    Považská Bystrica is a town in northwestern Slovakia known as an industrial center situated in a valley surrounded by the Strážov Mountains.
  • E. Košice
    Košice is a major city in eastern Slovakia known for its historic Old Town, Gothic St. Elisabeth Cathedral, and role as an important cultural and economic center.
  • 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_69c0087361a48190905c6b55969852b8 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04f528acc8190bc6943d812460b57 completed March 22, 2026, 8:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6636b8a388190879829af44325e0e completed March 27, 2026, 11 a.m.
Created at: March 22, 2026, 4:06 p.m.