Triple
T2637951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zora |
E62792
|
entity |
| Predicate | isGivenNameOf |
P17
|
FINISHED |
| Object |
Zora Vesecká
Zora Vesecká is a Czech individual whose given name is Zora, a common female name in Slavic countries.
|
E283710
|
NE FINISHED |
How this triple was built (4 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: Zora Vesecká | Statement: [Zora, isGivenNameOf, Zora Vesecká]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zora Vesecká Context triple: [Zora, isGivenNameOf, Zora Vesecká]
-
A.
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.
-
B.
Terézia Mora
Terézia Mora is a Hungarian-born German writer and translator acclaimed for her innovative prose and contributions to contemporary German-language literature.
-
C.
Milena Králíčková
Milena Králíčková is a Czech academic and physician who serves as the rector of Charles University in Prague.
-
D.
Júlia Justína Zavacká
Júlia Justína Zavacká, later known as Julia Warhola, was the mother of American artist Andy Warhol and an important influence on his life and work.
-
E.
Hana Benešová
Hana Benešová was the wife of Czechoslovak statesman and second president Edvard Beneš and served as the country's First Lady during his presidencies.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Zora Vesecká Triple: [Zora, isGivenNameOf, Zora Vesecká]
Generated description
Zora Vesecká is a Czech individual whose given name is Zora, a common female name in Slavic countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zora Vesecká Target entity description: Zora Vesecká is a Czech individual whose given name is Zora, a common female name in Slavic countries.
-
A.
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.
-
B.
Terézia Mora
Terézia Mora is a Hungarian-born German writer and translator acclaimed for her innovative prose and contributions to contemporary German-language literature.
-
C.
Milena Králíčková
Milena Králíčková is a Czech academic and physician who serves as the rector of Charles University in Prague.
-
D.
Júlia Justína Zavacká
Júlia Justína Zavacká, later known as Julia Warhola, was the mother of American artist Andy Warhol and an important influence on his life and work.
-
E.
Hana Benešová
Hana Benešová was the wife of Czechoslovak statesman and second president Edvard Beneš and served as the country's First Lady during his presidencies.
- F. None of above. chosen
Provenance (5 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd8e470ac8190bd0d6de6805afcd0 |
completed | March 7, 2026, 7:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af90b3e9b48190857ae21022a4fb15 |
completed | March 10, 2026, 3:32 a.m. |
| NEDg | Description generation | batch_69af922043508190a9a9ceced2425109 |
completed | March 10, 2026, 3:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af927bb1d0819081ab11eb4470e28d |
completed | March 10, 2026, 3:39 a.m. |
Created at: March 6, 2026, 9:53 p.m.