Triple
T5946381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magda Gabor |
E132291
|
entity |
| Predicate | nameInNativeLanguage |
P1435
|
FINISHED |
| Object | Gábor Magda |
E58577
|
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: Gábor Magda | Statement: [Magda Gabor, nameInNativeLanguage, Gábor Magda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gábor Magda Context triple: [Magda Gabor, nameInNativeLanguage, Gábor Magda]
-
A.
Vilmos Gábor
Vilmos Gábor was the father of Hungarian-American actress and socialite Zsa Zsa Gabor.
-
B.
Toma Erdődy
Toma Erdődy was a Croatian nobleman and military leader best known for his role in defending Habsburg territories against the Ottoman Empire in the late 16th century.
-
C.
László Papp
László Papp was a legendary Hungarian boxer who became the first boxer to win three consecutive Olympic gold medals.
-
D.
Ákos Eleőd
Ákos Eleőd is a Hungarian architect best known for designing Budapest’s Memento Park, an open-air museum dedicated to statues and monuments from the country’s communist era.
-
E.
Gábor
chosen
Gábor is a Hungarian masculine given name, commonly used as the local form of Gabriel.
- 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_69c1355102c88190b139ba052e12a875 |
completed | March 23, 2026, 12:42 p.m. |
Created at: March 22, 2026, 4:01 p.m.