Triple
T15516202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nastia Liukin |
E368839
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object |
Anna Kotchneva
Anna Kotchneva is a former Soviet rhythmic gymnast and the mother of Olympic champion Nastia Liukin.
|
E1170533
|
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: Anna Kotchneva | Statement: [Nastia Liukin, mother, Anna Kotchneva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Kotchneva Context triple: [Nastia Liukin, mother, Anna Kotchneva]
-
A.
Anna Astrakhantseva
Anna Astrakhantseva is an actress known for her role in the film "Two Women."
-
B.
Katerina Tikhomirova
Katerina Tikhomirova is the ambitious, resilient female protagonist of the Soviet film "Moscow Does Not Believe in Tears," whose life in Moscow reflects themes of love, career, and personal independence.
-
C.
Maria Khoreva
Maria Khoreva is a prominent Russian ballerina and Mariinsky Theatre principal dancer renowned for her virtuosity and classical Vaganova training.
-
D.
Anna Koltovskaya
Anna Koltovskaya was a Russian noblewoman best known as one of the later wives of Tsar Ivan IV (Ivan the Terrible) of Russia.
-
E.
Tatiana Groshkova
Tatiana Groshkova is a former Soviet artistic gymnast known for her powerful tumbling and contributions to the dominant Soviet women’s gymnastics program in the late 1980s.
- 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: Anna Kotchneva Triple: [Nastia Liukin, mother, Anna Kotchneva]
Generated description
Anna Kotchneva is a former Soviet rhythmic gymnast and the mother of Olympic champion Nastia Liukin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anna Kotchneva Target entity description: Anna Kotchneva is a former Soviet rhythmic gymnast and the mother of Olympic champion Nastia Liukin.
-
A.
Anna Astrakhantseva
Anna Astrakhantseva is an actress known for her role in the film "Two Women."
-
B.
Katerina Tikhomirova
Katerina Tikhomirova is the ambitious, resilient female protagonist of the Soviet film "Moscow Does Not Believe in Tears," whose life in Moscow reflects themes of love, career, and personal independence.
-
C.
Maria Khoreva
Maria Khoreva is a prominent Russian ballerina and Mariinsky Theatre principal dancer renowned for her virtuosity and classical Vaganova training.
-
D.
Anna Koltovskaya
Anna Koltovskaya was a Russian noblewoman best known as one of the later wives of Tsar Ivan IV (Ivan the Terrible) of Russia.
-
E.
Tatiana Groshkova
Tatiana Groshkova is a former Soviet artistic gymnast known for her powerful tumbling and contributions to the dominant Soviet women’s gymnastics program in the late 1980s.
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e04033303c8190a87b6384f68a6921 |
completed | April 16, 2026, 1:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ec6b5ac8190abeb944857d912e6 |
completed | May 9, 2026, 5:28 p.m. |
| NEDg | Description generation | batch_69ff6fc55c2c8190a94517888143ee61 |
completed | May 9, 2026, 5:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff703fe0088190ab5578d3d398ca09 |
completed | May 9, 2026, 5:34 p.m. |
Created at: April 10, 2026, 4:02 a.m.