Triple
T4211346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hana Benešová |
E93908
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Hana 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: Hana Benešová | Statement: [Hana Benešová, name, Hana Benešová]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hana Benešová Context triple: [Hana Benešová, name, Hana 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.
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.
-
C.
Eva Ondříčková
Eva Ondříčková is known as the wife of acclaimed Czech cinematographer Miroslav Ondříček.
-
D.
Milena Králíčková
Milena Králíčková is a Czech academic and physician who serves as the rector of Charles University in Prague.
-
E.
Dana Zátopková
Dana Zátopková was a Czech javelin thrower and Olympic champion, renowned both for her athletic achievements and as the wife of legendary runner Emil Zátopek.
- 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_69b5a852e0448190bc488087e92a94d4 |
completed | March 14, 2026, 6:26 p.m. |
Created at: March 12, 2026, 11:04 p.m.