Triple
T2251315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evgeni Malkin |
E49622
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Evgeni
Evgeni is a masculine given name most notably associated with Russian-born NHL star Evgeni Malkin.
|
E246656
|
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: Evgeni | Statement: [Evgeni Malkin, givenName, Evgeni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Evgeni Context triple: [Evgeni Malkin, givenName, Evgeni]
-
A.
Igor Babuschkin
Igor Babuschkin is an AI researcher and engineer known for his work on large language models at organizations such as DeepMind, OpenAI, and later xAI.
-
B.
Dimitri
Dimitri is a masculine given name of Greek origin, commonly used in various cultures and languages.
-
C.
Maxim Afinogenov
Maxim Afinogenov is a Russian former professional ice hockey right winger best known for his speedy NHL career, primarily with the Buffalo Sabres.
-
D.
Andrey Voronikhin
Andrey Voronikhin was a prominent Russian neoclassical architect of the late 18th and early 19th centuries, noted for shaping the architectural landscape of St. Petersburg.
-
E.
Kirill Shubsky
Kirill Shubsky is a Russian businessman known primarily as the husband of actress and model Anastasia Shubskaya.
- 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: Evgeni Triple: [Evgeni Malkin, givenName, Evgeni]
Generated description
Evgeni is a masculine given name most notably associated with Russian-born NHL star Evgeni Malkin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Evgeni Target entity description: Evgeni is a masculine given name most notably associated with Russian-born NHL star Evgeni Malkin.
-
A.
Igor Babuschkin
Igor Babuschkin is an AI researcher and engineer known for his work on large language models at organizations such as DeepMind, OpenAI, and later xAI.
-
B.
Dimitri
Dimitri is a masculine given name of Greek origin, commonly used in various cultures and languages.
-
C.
Maxim Afinogenov
Maxim Afinogenov is a Russian former professional ice hockey right winger best known for his speedy NHL career, primarily with the Buffalo Sabres.
-
D.
Andrey Voronikhin
Andrey Voronikhin was a prominent Russian neoclassical architect of the late 18th and early 19th centuries, noted for shaping the architectural landscape of St. Petersburg.
-
E.
Kirill Shubsky
Kirill Shubsky is a Russian businessman known primarily as the husband of actress and model Anastasia Shubskaya.
- 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_69a88aaa9250819095e127d0d77e8a32 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc11d04688190abc04fac3a1804a9 |
completed | March 7, 2026, 6:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6b1bc424819087b2ce9a6256a180 |
completed | March 9, 2026, 6:39 a.m. |
| NEDg | Description generation | batch_69ae6be0d108819085cf8c531d08db65 |
completed | March 9, 2026, 6:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae6c0fc220819090b254cc20b1bc26 |
completed | March 9, 2026, 6:43 a.m. |
Created at: March 4, 2026, 7:47 p.m.