Triple
T15152886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | János Schulek |
E361993
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | János |
E286726
|
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: János | Statement: [János Schulek, givenName, János]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: János Context triple: [János Schulek, givenName, János]
-
A.
János
chosen
János is the Hungarian form of the given name John, commonly used in Hungary and among Hungarian speakers.
-
B.
József
József is a Hungarian masculine given name equivalent to Joseph, commonly used in Hungary and among Hungarian communities.
-
C.
Lajos
Lajos is a Hungarian masculine given name commonly used in Central and Eastern Europe.
-
D.
István
István is the Hungarian given name of Stephen I of Hungary, the first Christian king and founder of the medieval Hungarian state.
-
E.
Jozef
Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00609040081908c849475a2fa6443 |
completed | April 15, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56b25a808190b56f8ab3c506b771 |
completed | May 9, 2026, 3:45 p.m. |
Created at: April 10, 2026, 3:07 a.m.