Triple

T16256144
Position Surface form Disambiguated ID Type / Status
Subject Most Basin E394632 entity
Predicate containsCity P294 FINISHED
Object Litvínov E752885 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: Litvínov | Statement: [Most Basin, containsCity, Litvínov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Litvínov
Context triple: [Most Basin, containsCity, Litvínov]
  • A. Litvínov chosen
    Litvínov is an industrial town in the north of the Czech Republic known for its chemical industry and ice hockey tradition.
  • B. Litavka
    Litavka is a river in the Czech Republic that flows through the town of Beroun before joining the Berounka River.
  • C. Lišov
    Lišov is a small town in the South Bohemian Region of the Czech Republic, known for its traditional architecture and rural Central European character.
  • D. Stropkov
    Stropkov is a small town in northeastern Slovakia known for its location in the Ondava River valley and its historical and cultural heritage.
  • E. Kriváň
    Kriváň is a prominent and symbolically important peak in Slovakia’s High Tatras, often regarded as a national symbol and popular hiking destination.
  • 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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2459a48f081909c76b38741b8f04e completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000ee9bc4c8190bb7e54ed2ad162b3 completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 5:04 a.m.