Triple
T13016517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ján Svatopluk Presl |
E322565
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ján |
E929888
|
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: Ján | Statement: [Ján Svatopluk Presl, givenName, Ján]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ján Context triple: [Ján Svatopluk Presl, givenName, Ján]
-
A.
Ján
chosen
Ján is a common Slovak male given name, equivalent to "John" in English.
-
B.
Jozef
Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
-
C.
János
János is the Hungarian form of the given name John, commonly used in Hungary and among Hungarian speakers.
-
D.
Štefan
Štefan is the Slovak form of the given name Stephen, commonly used in Slovakia and other Slovak-speaking communities.
-
E.
Jaroslav
Jaroslav is a masculine given name of Slavic origin, commonly used in Czech, Slovak, Polish, and other Slavic languages.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ecd04748190ade2530ee5db35fe |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c1147974819090007c21383d5c86 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 9, 2026, 8:51 p.m.