Triple

T653580
Position Surface form Disambiguated ID Type / Status
Subject Spisz E11396 entity
Predicate hasMajorTown P316 FINISHED
Object Levoča E102333 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: Levoča | Statement: [Spisz, hasMajorTown, Levoča]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Levoča
Context triple: [Spisz, hasMajorTown, Levoča]
  • A. 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.
  • B. Ružomberok
    Ružomberok is a town in northern Slovakia known for its location in the Liptov region and its historical and cultural significance.
  • C. Kežmarok chosen
    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. Spišská Nová Ves
    Spišská Nová Ves is a town in eastern Slovakia known as a cultural and economic center of the Spiš region and as a gateway to the Slovak Paradise National Park.
  • E. Zlín
    Zlín is a city in the Czech Republic known for its modernist architecture and historical association with the Baťa shoe company.
  • 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_69a493266a2881909daf4c40f719dee8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f4a660c8190b887cb4da01ef7ae completed March 1, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7b8341cf0819089d18c2c63192679 completed March 4, 2026, 4:42 a.m.
Created at: March 1, 2026, 7:36 p.m.