Triple
T6026677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victoria |
E134198
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | Viktoria |
E355903
|
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: Viktoria | Statement: [Victoria, relatedTo, Viktoria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viktoria Context triple: [Victoria, relatedTo, 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.
Rositsa
Rositsa is a river in northern Bulgaria that serves as a significant tributary of the Yantra River.
- 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0560cdc308190b25ca8ecb42c4e4f |
completed | March 22, 2026, 8:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c113799d648190a08516a33a5f92b7 |
completed | March 23, 2026, 10:18 a.m. |
Created at: March 22, 2026, 4:07 p.m.