Triple
T8271269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kulik |
E193432
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Irina Kulik
Irina Kulik is a Russian art critic, journalist, and lecturer known for her work on contemporary art and culture.
|
E734108
|
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: Irina Kulik | Statement: [Kulik, hasNotableBearer, Irina Kulik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Irina Kulik Context triple: [Kulik, hasNotableBearer, Irina Kulik]
-
A.
Irina Sobyanina
Irina Sobyanina is the former wife of Sergei Sobyanin, the long-serving mayor of Moscow and prominent Russian politician.
-
B.
Daria Kulik
Daria Kulik is the daughter of Russian Olympic figure skating champion Ilia Kulik.
-
C.
Irina Baronova
Irina Baronova was a renowned Russian-born ballerina, celebrated as one of the legendary "Baby Ballerinas" of the Ballets Russes de Monte Carlo in the 1930s.
-
D.
Natalia Staritskaya
Natalia Staritskaya was the wife of prominent Russian and Soviet scientist Vladimir Vernadsky, known for her role in his personal and family life.
-
E.
Svetlana Gannushkina
Svetlana Gannushkina is a prominent Russian human rights activist known for her work defending the rights of refugees, migrants, and victims of conflict in the North Caucasus.
- 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: Irina Kulik Triple: [Kulik, hasNotableBearer, Irina Kulik]
Generated description
Irina Kulik is a Russian art critic, journalist, and lecturer known for her work on contemporary art and culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Irina Kulik Target entity description: Irina Kulik is a Russian art critic, journalist, and lecturer known for her work on contemporary art and culture.
-
A.
Irina Sobyanina
Irina Sobyanina is the former wife of Sergei Sobyanin, the long-serving mayor of Moscow and prominent Russian politician.
-
B.
Daria Kulik
Daria Kulik is the daughter of Russian Olympic figure skating champion Ilia Kulik.
-
C.
Irina Baronova
Irina Baronova was a renowned Russian-born ballerina, celebrated as one of the legendary "Baby Ballerinas" of the Ballets Russes de Monte Carlo in the 1930s.
-
D.
Natalia Staritskaya
Natalia Staritskaya was the wife of prominent Russian and Soviet scientist Vladimir Vernadsky, known for her role in his personal and family life.
-
E.
Svetlana Gannushkina
Svetlana Gannushkina is a prominent Russian human rights activist known for her work defending the rights of refugees, migrants, and victims of conflict in the North Caucasus.
- 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_69ca82e14ae481908ffdb822cd2192bc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7986f8cc8190a529dda980dd6e98 |
completed | March 31, 2026, 7:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1cd748708190a353469043f3046a |
completed | April 2, 2026, 7:37 a.m. |
| NEDg | Description generation | batch_69ce1e3a269481908ea191ff28ea1313 |
completed | April 2, 2026, 7:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce1ef9fb208190a50b4d8a595f5fdb |
completed | April 2, 2026, 7:47 a.m. |
Created at: March 30, 2026, 5:50 p.m.