Triple
T15516139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dennis Gabor |
E368838
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gabor |
E741308
|
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: Gabor | Statement: [Dennis Gabor, familyName, Gabor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabor Context triple: [Dennis Gabor, familyName, Gabor]
-
A.
Gabor
chosen
Gabor is a Hungarian surname most famously associated with the entertainment family that includes actresses Eva and Zsa Zsa Gabor.
-
B.
Kalmus
Kalmus is a surname most notably associated with Herbert Kalmus, the co-founder of the pioneering color motion picture company Technicolor.
-
C.
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.
-
D.
Burrus
Burrus is a variant form of the name Burr, used as a personal or family name.
-
E.
Erwin
Erwin is a masculine given name of German origin, historically associated with figures such as the World War II field marshal Erwin Rommel.
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e04033303c8190a87b6384f68a6921 |
completed | April 16, 2026, 1:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d5111648190a61fc87170b0d93c |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 4:02 a.m.