Triple
T6115248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olga |
E136344
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Ólga |
E136344
|
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: Ólga | Statement: [Olga, hasVariant, Ólga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ólga Context triple: [Olga, hasVariant, Ólga]
-
A.
Olga
chosen
Olga is a female given name of Russian origin, historically borne by several notable figures including Russian grand duchesses and saints.
-
B.
Ottilia
Ottilia is a feminine given name of Germanic origin, related to Otto and typically interpreted to mean "wealth" or "prosperity."
-
C.
Rositsa
Rositsa is a river in northern Bulgaria that serves as a significant tributary of the Yantra River.
-
D.
Galina
Galina is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
-
E.
Margareta
Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
- 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_69c0089ea6f88190b349be53e04b4f5f |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05bc0bee08190ab93eae34ea8cdde |
completed | March 22, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1256aa9f8819090fdc98343af6f8e |
completed | March 23, 2026, 11:35 a.m. |
Created at: March 22, 2026, 4:14 p.m.