Triple
T5946379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magda Gabor |
E132291
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Magdolna |
E200104
|
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: Magdolna | Statement: [Magda Gabor, givenName, Magdolna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magdolna Context triple: [Magda Gabor, givenName, Magdolna]
-
A.
Magda
chosen
Magda is a feminine given name, commonly used as a short form of Magdalena in various European languages.
-
B.
Katalin
Katalin is a Hungarian given name most prominently associated with biochemist Katalin Karikó, a pioneer of mRNA technology used in COVID-19 vaccines.
-
C.
Margareta
Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
-
D.
Mária
Mária is the Hungarian and Slovak form of the given name Mary, commonly used in Central and Eastern Europe.
-
E.
Sarolt
Sarolt was a prominent 10th-century Hungarian noblewoman and duchess, influential in the Christianization and early state formation of Hungary as the wife of Grand Prince Géza and mother of King Stephen I.
- 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0393bd4488190bba68d9c6e872e04 |
completed | March 22, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c08a11f48190b16ca30842f23ce5 |
completed | March 23, 2026, 4:24 a.m. |
Created at: March 22, 2026, 4:01 p.m.