Triple

T4211348
Position Surface form Disambiguated ID Type / Status
Subject Hana Benešová E93908 entity
Predicate familyName P18 FINISHED
Object Benešová E93908 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: Benešová | Statement: [Hana Benešová, familyName, Benešová]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Benešová
Context triple: [Hana Benešová, familyName, Benešová]
  • A. Hana Benešová chosen
    Hana Benešová was the wife of Czechoslovak statesman and second president Edvard Beneš and served as the country's First Lady during his presidencies.
  • B. Zelníčková
    Zelníčková is a Czech surname, notably borne by Ivana Marie Zelníčková, the Czech-American businesswoman and former wife of Donald Trump.
  • C. 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.
  • D. Dana Vávrová
    Dana Vávrová was a Czech-born German actress and film director known for her acclaimed performances in European cinema and collaborations with director Joseph Vilsmaier.
  • E. Milena Králíčková
    Milena Králíčková is a Czech academic and physician who serves as the rector of Charles University in Prague.
  • 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_69b3451743608190808f41d17ccf2650 completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b3481219a08190b17bf3b414bd7d4a completed March 12, 2026, 11:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b76f07b4819097b59868af43b611 completed March 14, 2026, 7:30 p.m.
Created at: March 12, 2026, 11:04 p.m.