Triple
T4981712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giorgio |
E111900
|
entity |
| Predicate | hasCognate |
P2525
|
FINISHED |
| Object | György |
E411309
|
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: György | Statement: [Giorgio, hasCognate, György]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: György Context triple: [Giorgio, hasCognate, György]
-
A.
György
chosen
György is a Hungarian given name commonly used for men, equivalent to the English name George.
-
B.
Gábor
Gábor is a Hungarian masculine given name, commonly used as the local form of Gabriel.
-
C.
László
László is a Hungarian given name most famously borne by the avant-garde artist and Bauhaus teacher László Moholy-Nagy.
-
D.
Béla
Béla was a common medieval Hungarian royal given name borne by several kings, most notably Béla IV of Hungary.
-
E.
Jenő
Jenő is the Hungarian given name of the renowned theoretical physicist and mathematician Wigner Jenő Pál, known in English as Eugene Wigner.
- 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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd725310088190a44b5c02658edc52 |
completed | March 20, 2026, 4:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be8a0f90048190998dad99555891c0 |
completed | March 21, 2026, 12:07 p.m. |
Created at: March 20, 2026, 1:33 p.m.