Triple
T9663162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nagy |
E233636
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
Nagyová (feminine form in Slovak and Czech)
Nagyová is the Slovak and Czech feminine surname form derived from the Hungarian-origin surname Nagy.
|
E813941
|
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: Nagyová (feminine form in Slovak and Czech) | Statement: [Nagy, hasVariant, Nagyová (feminine form in Slovak and Czech)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagyová (feminine form in Slovak and Czech) Context triple: [Nagy, hasVariant, Nagyová (feminine form in Slovak and Czech)]
-
A.
Zelníčková
Zelníčková is a Czech surname, notably borne by Ivana Marie Zelníčková, the Czech-American businesswoman and former wife of Donald Trump.
-
B.
Saltykova
Saltykova is a Russian surname most notoriously associated with Darya Saltykova, an 18th-century noblewoman and serial killer.
-
C.
Pekarová
Pekarová is a Czech or Slovak feminine surname derived from the masculine form Pekar.
-
D.
Nosková
Nosková is a Czech surname, typically the feminine form of the surname Nosek.
-
E.
Fischerová
Fischerová is a Czech feminine surname derived from the German surname Fischer, commonly borne by women in Czech-speaking regions.
- 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: Nagyová (feminine form in Slovak and Czech) Triple: [Nagy, hasVariant, Nagyová (feminine form in Slovak and Czech)]
Generated description
Nagyová is the Slovak and Czech feminine surname form derived from the Hungarian-origin surname Nagy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nagyová (feminine form in Slovak and Czech) Target entity description: Nagyová is the Slovak and Czech feminine surname form derived from the Hungarian-origin surname Nagy.
-
A.
Zelníčková
Zelníčková is a Czech surname, notably borne by Ivana Marie Zelníčková, the Czech-American businesswoman and former wife of Donald Trump.
-
B.
Saltykova
Saltykova is a Russian surname most notoriously associated with Darya Saltykova, an 18th-century noblewoman and serial killer.
-
C.
Pekarová
Pekarová is a Czech or Slovak feminine surname derived from the masculine form Pekar.
-
D.
Nosková
Nosková is a Czech surname, typically the feminine form of the surname Nosek.
-
E.
Fischerová
Fischerová is a Czech feminine surname derived from the German surname Fischer, commonly borne by women in Czech-speaking regions.
- 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_69ca848d3b6c8190ae98ea554dea58df |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9c0cde048190b5a8e1548825d4d9 |
completed | April 1, 2026, 10:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18a1422348190967943b0d4da8efd |
completed | April 4, 2026, 10 p.m. |
| NEDg | Description generation | batch_69d18b66e79881909228aa3e1e34af26 |
completed | April 4, 2026, 10:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d18bbfb1808190bd7f7ff4326af72c |
completed | April 4, 2026, 10:07 p.m. |
Created at: March 30, 2026, 8:14 p.m.