Triple
T16066121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Károly Király |
E389735
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Károly Király |
E389735
|
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 Király | Statement: [Károly Király, name, Károly Király]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Károly Király Context triple: [Károly Király, name, Károly Király]
-
A.
Károly Király
chosen
Károly Király was a Romanian Hungarian politician and minority rights advocate who served in various leadership roles during and after the communist era in Romania.
-
B.
Károly Grósz
Károly Grósz was a Hungarian communist politician who served as the last hardline General Secretary of the Hungarian Socialist Workers' Party during the late 1980s transition period.
-
C.
Gyula Jankovits
Gyula Jankovits was a Hungarian sculptor best known for creating prominent public monuments in Budapest, including the Gellért Monument.
-
D.
Károly Palotai
Károly Palotai was a Hungarian football referee and former player renowned for officiating major international matches, including World Cup games and European club finals.
-
E.
Pál Nagy
Pál Nagy is a Hungarian name shared by several notable individuals, including figures in fields such as sports, academia, and public life.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837ca628819081dfc439fe322d58 |
completed | April 17, 2026, 12:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff798c2a48190b6eccd476a0a396f |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 4:57 a.m.