Triple
T5360473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria |
E103006
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Mariya (Cyrillic: Мария) |
E108095
|
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: Mariya (Cyrillic: Мария) | Statement: [Maria, hasVariant, Mariya (Cyrillic: Мария)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mariya (Cyrillic: Мария) Context triple: [Maria, hasVariant, Mariya (Cyrillic: Мария)]
-
A.
Marya
Marya is a feminine given name, often considered a variant of Mary and used in various cultures and languages.
-
B.
Maria Maria
"Maria Maria" is a Latin rock and R&B-influenced hit song by Santana featuring The Product G&B that became one of the defining tracks of the late 1990s and early 2000s.
-
C.
Marija
chosen
Marija is a feminine given name commonly used in Slavic and other European cultures, equivalent to "Maria" or "Mary."
-
D.
Lyudmila
Lyudmila is a Russian linguist and the former First Lady of Russia, known for being the ex-wife of President Vladimir Putin.
-
E.
Bogorodica
Bogorodica is a small settlement in the Gevgelija region of southeastern North Macedonia, known for its proximity to the Greek border and its role as a local transit point.
- 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd86588af081908c846fcde65724da |
completed | March 20, 2026, 5:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf21ec83b88190abc227d93b4c1c49 |
completed | March 21, 2026, 10:55 p.m. |
Created at: March 20, 2026, 2:02 p.m.