Triple
T13087917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferenc |
E310384
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Ferencz |
E378878
|
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: Ferencz | Statement: [Ferenc, relatedName, Ferencz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ferencz Context triple: [Ferenc, relatedName, Ferencz]
-
A.
Ferenc
chosen
Ferenc is a Hungarian masculine given name, equivalent to Francis in English.
-
B.
Friesz
Friesz is a surname most notably associated with the French Fauvist painter Othon Friesz.
-
C.
Ferenc (Hungarian)
Ferenc is the Hungarian given name equivalent to Francisco, commonly used as a male first name in Hungary.
-
D.
Zoltán
Zoltán was an early medieval Hungarian ruler, traditionally regarded as one of the first princes of the Principality of Hungary and a successor in the Árpád dynasty.
-
E.
Ferdl
Ferdl is a German diminutive form of the male given name Ferdinand, commonly used as an affectionate nickname.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d981378dd08190b4f00e4e5df0e480 |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d614704481908758cf8691a941ea |
completed | May 3, 2026, 4:59 a.m. |
Created at: April 9, 2026, 9:02 p.m.