Triple
T14148229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zala György |
E350607
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | György Zala |
E350607
|
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 Zala | Statement: [Zala György, name, György Zala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: György Zala Context triple: [Zala György, name, György Zala]
-
A.
Zala György
chosen
Zala György was a Hungarian sculptor best known for his monumental public statues and memorials in Budapest at the turn of the 20th century.
-
B.
Gyula Halász
Gyula Halász, better known by his pseudonym Brassaï, was a Hungarian–French photographer famed for his evocative black-and-white images of Parisian nightlife in the 1930s.
-
C.
Vilmos Gábor
Vilmos Gábor was the father of Hungarian-American actress and socialite Zsa Zsa Gabor.
-
D.
Ernő Gerő
Ernő Gerő was a hardline Hungarian communist leader and brief de facto head of state whose intransigent policies and actions helped trigger the 1956 Hungarian Revolution.
-
E.
Miklós Lázár
Miklós Lázár is an actor known for his role in the supernatural crime thriller film "The First Power."
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61237ef481909374c1f68a2370b7 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd2802ba608190849313ff2661cd07 |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 12:55 a.m.