Triple
T13821616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Béla Balázs |
E332150
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Béla |
E383704
|
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: Béla | Statement: [Béla Balázs, givenName, Béla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Béla Context triple: [Béla Balázs, givenName, Béla]
-
A.
Béla
chosen
Béla was a common medieval Hungarian royal given name borne by several kings, most notably Béla IV of Hungary.
-
B.
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.
-
C.
Lajos
Lajos is a Hungarian masculine given name commonly used in Central and Eastern Europe.
-
D.
György
György is a Hungarian given name commonly used for men, equivalent to the English name George.
-
E.
András
András is the Hungarian given name of Andrew S. Grove, the influential former CEO and co-founder of Intel.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0284428081908043c55caeefb833 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b8e60e1c81908d51d723e85e0541 |
completed | May 3, 2026, 9:06 p.m. |
Created at: April 9, 2026, 10:12 p.m.