Triple
T22251622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zsófia |
E549991
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Zsofía |
—
|
NE NERFINISHED |
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: Zsofía | Statement: [Zsófia, hasVariantSpelling, Zsofía]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zsofía Context triple: [Zsófia, hasVariantSpelling, Zsofía]
-
A.
Zsófia
chosen
Zsófia is the Hungarian form of the female given name Sophie, commonly used in Hungary and among Hungarian speakers.
-
B.
Orsolya
Orsolya is a Hungarian feminine given name equivalent to Ursula, traditionally associated with the Latin meaning “little she-bear.”
-
C.
Katalin
Katalin is a Hungarian given name most prominently associated with biochemist Katalin Karikó, a pioneer of mRNA technology used in COVID-19 vaccines.
-
D.
Mária
Mária is the Hungarian and Slovak form of the given name Mary, commonly used in Central and Eastern Europe.
-
E.
Piroska of Hungary
Piroska of Hungary, later known as Empress Irene, was a Hungarian princess who became Byzantine empress consort and an important religious patron after marrying Emperor John II Komnenos.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e41d9408190bd770cf282e22753 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138befa208190877760dec1896740 |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 16, 2026, 8:39 p.m.