Triple
T22639179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Viktoria Luise of Prussia |
E558773
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Viktoria |
—
|
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: Viktoria | Statement: [Princess Viktoria Luise of Prussia, givenName, Viktoria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viktoria Context triple: [Princess Viktoria Luise of Prussia, givenName, Viktoria]
-
A.
Viktoria
chosen
Viktoria is a feminine given name of Latin origin, commonly used in various European countries as a variant of "Victoria."
-
B.
Viktorka
Viktorka is the popular nickname of FC Viktoria Plzeň, a professional football club from Plzeň in the Czech Republic.
-
C.
Vladimira
Vladimira is a feminine given name, primarily used in Slavic cultures, derived from the male name Vladimir.
-
D.
Vika
Vika is a central neighborhood in Oslo, Norway, known for its waterfront location, cultural institutions, and proximity to the city’s business district.
-
E.
Victoriei
Victoriei is a major Bucharest Metro interchange station serving as an important transit hub in Romania’s capital city.
- 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1700f9fac8190b82190a54be22413 |
completed | April 29, 2026, 2:42 a.m. |
Created at: April 17, 2026, 3:04 p.m.