Triple

T4704761
Position Surface form Disambiguated ID Type / Status
Subject Váh E104365 entity
Predicate flowsThrough P225 FINISHED
Object Trenčín E78081 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: Trenčín | Statement: [Váh, flowsThrough, Trenčín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trenčín
Context triple: [Váh, flowsThrough, Trenčín]
  • A. Trenčín chosen
    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.
  • B. 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."
  • C. Kežmarok
    Kežmarok is a historic town in northern Slovakia known for its well-preserved medieval architecture and role as a cultural center of the Spiš (Spisz) region.
  • D. Žilina
    Žilina is a city in northwestern Slovakia that serves as an important industrial and transportation hub, particularly for rail connections in the region.
  • E. 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.
  • 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_69bd43e9b88481908582103dcadff3d9 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd63d1e9c48190bad5f7d68bf0f622 completed March 20, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67bb17e0819099a6d4f3ca54f616 completed March 21, 2026, 9:41 a.m.
Created at: March 20, 2026, 1:17 p.m.