Triple

T4638050
Position Surface form Disambiguated ID Type / Status
Subject Morava E101581 entity
Predicate hasTributary P415 FINISHED
Object Haná E382461 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: Haná | Statement: [Morava, hasTributary, Haná]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haná
Context triple: [Morava, hasTributary, Haná]
  • A. Haná chosen
    Haná is a historical ethnographic region in central Moravia in the Czech Republic, known for its fertile agricultural land, distinctive folk traditions, and Hanakian dialect.
  • B. Libuše
    Libuše is a Czech opera by Bedřich Smetana, centered on the legendary princess Libuše who prophesies the glory of Prague and the Czech nation.
  • C. Nosková
    Nosková is a Czech surname, typically the feminine form of the surname Nosek.
  • D. Hodonín
    Hodonín is a town in the South Moravian Region of the Czech Republic, notable as the birthplace of the first Czechoslovak president Tomáš Garrigue Masaryk.
  • E. Háje
    Háje is a Prague Metro station serving as the southern terminus of Line C in the Háje district of the city.
  • 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_69bd43d3bc7c81908f81fcf380476b0f completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a64214481908a207e8070cc7a45 completed March 20, 2026, 2:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfacf3cb08190a080e5ed1063902f completed March 21, 2026, 1:56 a.m.
Created at: March 20, 2026, 1:13 p.m.