Triple

T17009615
Position Surface form Disambiguated ID Type / Status
Subject Libuše E412662 entity
Predicate hasTitleRole P78808 FINISHED
Object Libuše E412662 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: Libuše | Statement: [Libuše, hasTitleRole, Libuše]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Libuše
Context triple: [Libuše, hasTitleRole, Libuše]
  • A. Libuše chosen
    Libuše is a Czech opera by Bedřich Smetana, centered on the legendary princess Libuše who prophesies the glory of Prague and the Czech nation.
  • B. Božena
    Božena is a Czech feminine given name most famously borne by the 19th-century writer Božena Němcová, a key figure in Czech literature and national revival.
  • C. Bechyně
    Bechyně is a historic spa town in the Czech Republic known for its ceramics tradition and picturesque location above the Lužnice River.
  • D. Nemšová
    Nemšová is a small town in western Slovakia known for its location near the Czech border and the Váh River within the Trenčín administrative area.
  • E. Lenka
    Lenka is a feminine given name, commonly used in Slavic countries, often as a diminutive or variant of names like Elena or Helena.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d47a8444819081f1262eb7dbda40 completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b46e89c81908271eb22b535c558 completed May 10, 2026, 11:56 p.m.
Created at: April 10, 2026, 5:33 a.m.