Triple
T21961581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | María |
E542342
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Marija |
—
|
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: Marija | Statement: [María, hasVariant, Marija]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marija Context triple: [María, hasVariant, Marija]
-
A.
Marija
chosen
Marija is a feminine given name commonly used in Slavic and other European cultures, equivalent to "Maria" or "Mary."
-
B.
Julijana
Julijana is a feminine given name, commonly used in Slavic countries, that corresponds to the name Juliana in other languages.
-
C.
Milica
Milica is the Slavic given name of actress and model Milla Jovovich, reflecting her Eastern European heritage.
-
D.
Emilija
Emilija is a feminine given name commonly used in various Slavic and Baltic countries, equivalent to Emilia or Emily in English.
-
E.
Majda
Majda is a surname most notably associated with Andrew J. Majda, an influential American mathematician known for his work in applied mathematics and partial differential equations.
- 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f124572738819098cc669aafa53cc6 |
completed | April 28, 2026, 9:19 p.m. |
Created at: April 16, 2026, 8 p.m.