Triple
T2985562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Károly Takács |
E80616
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Károly |
E79472
|
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: Károly | Statement: [Károly Takács, givenName, Károly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Károly Context triple: [Károly Takács, givenName, Károly]
-
A.
Károly
chosen
Károly is the Hungarian form of the given name Charles, commonly used as a male first name in Hungary.
-
B.
Kálmán
Kálmán is a Hungarian surname most notably associated with Rudolf E. Kálmán, the pioneering engineer and mathematician behind the Kalman filter.
-
C.
István
István is the Hungarian given name of Stephen I of Hungary, the first Christian king and founder of the medieval Hungarian state.
-
D.
Miklós
Miklós is a Hungarian masculine given name, equivalent to Nicholas in English.
-
E.
László
László is a Hungarian given name most famously borne by the avant-garde artist and Bauhaus teacher László Moholy-Nagy.
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99c76dfc8190b08bd6110ffabf25 |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e31a8188190bd5ad6c9757e7141 |
completed | March 11, 2026, 8:56 a.m. |
Created at: March 8, 2026, 2:59 p.m.