Triple
T6115270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olga |
E136344
|
entity |
| Predicate | scriptForm |
P9329
|
FINISHED |
| Object | Ольга |
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: Ольга | Statement: [Olga, scriptForm, Ольга]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ольга Context triple: [Olga, scriptForm, Ольга]
-
A.
Lyudmila
Lyudmila is a Russian linguist and the former First Lady of Russia, known for being the ex-wife of President Vladimir Putin.
-
B.
Olga
chosen
Olga is a female given name of Russian origin, historically borne by several notable figures including Russian grand duchesses and saints.
-
C.
Svetlana
Svetlana is a feminine given name of Slavic origin, most notably borne by Svetlana Alliluyeva, the daughter of Soviet leader Joseph Stalin.
-
D.
Ludmilla
Ludmilla is a coastal suburb of Darwin in Australia's Northern Territory, known for its residential areas and proximity to Fannie Bay.
-
E.
Ludmila
Ludmila is the heroine of Alexander Pushkin’s narrative poem "Ruslan and Ludmila," known as a beautiful Kievan princess whose abduction sets the story’s adventurous plot in motion.
- 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_69c6cae2c7f4819096354202532ae488 |
completed | March 27, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:14 p.m.