Triple
T16648035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ernö Rapée |
E404526
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ernö |
E563355
|
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: Ernö | Statement: [Ernö Rapée, givenName, Ernö]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ernö Context triple: [Ernö Rapée, givenName, Ernö]
-
A.
Ernő
chosen
Ernő is a Hungarian-born British modernist architect best known for his influential and often controversial Brutalist buildings in London.
-
B.
Béla
Béla was a common medieval Hungarian royal given name borne by several kings, most notably Béla IV of Hungary.
-
C.
Frigyes
Frigyes is a Hungarian masculine given name, notably borne by the influential mathematician Frigyes Riesz.
-
D.
Géza
Géza was a 10th-century Grand Prince of the Hungarians who played a key role in consolidating the Hungarian state and paving the way for its Christianization under his son Stephen I.
-
E.
Vilmos
Vilmos is a masculine given name of Hungarian origin, equivalent to William in English.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad794388190b2817d2ec5ff0de0 |
completed | April 18, 2026, 12:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d2f7ad88190ba85a79154502841 |
completed | May 10, 2026, 2:58 p.m. |
Created at: April 10, 2026, 5:18 a.m.