Triple

T11831401
Position Surface form Disambiguated ID Type / Status
Subject Trnava Region E281400 entity
Predicate hasCity P316 FINISHED
Object Trnava E470542 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: Trnava | Statement: [Trnava Region, hasCity, Trnava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trnava
Context triple: [Trnava Region, hasCity, Trnava]
  • A. Trnava chosen
    Trnava is a historic city in western Slovakia known for its well-preserved medieval center and numerous churches, earning it the nickname "Little Rome."
  • B. Trenčín
    Trenčín is a historic city in western Slovakia known for its medieval castle overlooking the Váh River and its role as a regional cultural and economic center.
  • C. 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.
  • 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. Prešov
    Prešov is a historic city in eastern Slovakia known for its preserved medieval center and role as a regional cultural and economic hub.
  • 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_69d6ab276f8c8190b1966a0ef11349ac completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a62c95988190a45dbaa7001c8846 completed April 10, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7941721d08190900ca872503055db completed May 3, 2026, 6:29 p.m.
Created at: April 8, 2026, 9:43 p.m.