Triple
T22174843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ștefan |
E548020
|
entity |
| Predicate | equivalentForm |
P6530
|
FINISHED |
| Object | Stefan |
—
|
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: Stefan | Statement: [Ștefan, equivalentForm, Stefan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stefan Context triple: [Ștefan, equivalentForm, Stefan]
-
A.
Stefan
Stefan is the given name of Saint Simeon the Myrrh-streaming, a revered medieval Serbian ruler and Orthodox Christian saint.
-
B.
Stefan
chosen
Stefan is a masculine given name of Slavic origin, commonly used in many European countries as a variant of Stephen.
-
C.
Stefan
Stefan is the protagonist of Eoin Colfer’s science-fiction novel "The Supernaturalist," a teenage boy who can see and combat parasitic creatures draining human life force in a dystopian future city.
-
D.
Stefan Friedrich
Stefan Friedrich is a German local politician who serves as the mayor of the municipality of Allensbach in Baden-Württemberg.
-
E.
Stefan Reinhardt
Stefan Reinhardt is a notable individual who shares the Reinhardt surname, recognized as a distinguished bearer of that family name.
- 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_69e11e3d53f88190a2b690e3f25bb062 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a6b755c81909e9bd2a588c065b3 |
completed | April 28, 2026, 9:45 p.m. |
Created at: April 16, 2026, 8:34 p.m.