Triple
T16073288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oksana |
E389917
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Oksana Dyka
Oksana Dyka is a Ukrainian operatic soprano acclaimed for her powerful voice and performances on major international opera stages.
|
E1208464
|
NE FINISHED |
How this triple was built (4 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: Oksana Dyka | Statement: [Oksana, hasNotableBearer, Oksana Dyka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oksana Dyka Context triple: [Oksana, hasNotableBearer, Oksana Dyka]
-
A.
Oksana Shachko
Oksana Shachko was a Ukrainian artist and feminist activist best known as one of the co-founders of the radical protest group FEMEN.
-
B.
Daria Kulik
Daria Kulik is the daughter of Russian Olympic figure skating champion Ilia Kulik.
-
C.
Natalya Andrejchenko
Natalya Andrejchenko is a Russian actress best known for her title role in the 1984 Soviet film "Mary Poppins, Goodbye."
-
D.
Tatjana Masurenko
Tatjana Masurenko is a distinguished violist and pedagogue known for her international solo career and influential teaching in Europe.
-
E.
Oksana Baiul
Oksana Baiul is a Ukrainian figure skater who became the 1994 Olympic ladies' singles champion and one of the sport's most celebrated performers.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Oksana Dyka Triple: [Oksana, hasNotableBearer, Oksana Dyka]
Generated description
Oksana Dyka is a Ukrainian operatic soprano acclaimed for her powerful voice and performances on major international opera stages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oksana Dyka Target entity description: Oksana Dyka is a Ukrainian operatic soprano acclaimed for her powerful voice and performances on major international opera stages.
-
A.
Oksana Shachko
Oksana Shachko was a Ukrainian artist and feminist activist best known as one of the co-founders of the radical protest group FEMEN.
-
B.
Daria Kulik
Daria Kulik is the daughter of Russian Olympic figure skating champion Ilia Kulik.
-
C.
Natalya Andrejchenko
Natalya Andrejchenko is a Russian actress best known for her title role in the 1984 Soviet film "Mary Poppins, Goodbye."
-
D.
Tatjana Masurenko
Tatjana Masurenko is a distinguished violist and pedagogue known for her international solo career and influential teaching in Europe.
-
E.
Oksana Baiul
Oksana Baiul is a Ukrainian figure skater who became the 1994 Olympic ladies' singles champion and one of the sport's most celebrated performers.
- F. None of above. chosen
Provenance (5 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183c0390c8190b0da263cccec14e5 |
completed | April 17, 2026, 12:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002d99e8ec8190945812327283ba6c |
completed | May 10, 2026, 7:02 a.m. |
| NEDg | Description generation | batch_6a002f237e9c819086f12b3cadd6f14c |
completed | May 10, 2026, 7:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a002fa14ee4819080b02b368c0080b9 |
completed | May 10, 2026, 7:11 a.m. |
Created at: April 10, 2026, 4:57 a.m.