Triple
T19850533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kogan |
E476979
|
entity |
| Predicate | hasAlternativeForm |
P455
|
FINISHED |
| Object |
Koganov
Koganov is a surname, likely of Slavic or Eastern European origin, used as a variant form of the name Kogan.
|
E1398038
|
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: Koganov | Statement: [Kogan, hasAlternativeForm, Koganov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koganov Context triple: [Kogan, hasAlternativeForm, Koganov]
-
A.
Gryzlov
Gryzlov is a Russian surname most prominently associated with Boris Gryzlov, a notable Russian politician and former chairman of the State Duma.
-
B.
Kozlov
Kozlov is a historic Russian town, now known as Michurinsk, that developed as a significant regional center of trade and agriculture.
-
C.
Kozlov
Kozlov is the former Russian name of the city now known as Gözleve (Eupatoria) in Crimea, reflecting its historical period under Russian influence.
-
D.
Kovalyov
Kovalyov is the absurdly unfortunate civil servant protagonist of Shostakovich’s opera “The Nose,” whose detached nose gains a higher social rank than he does.
-
E.
Chebutykin
Chebutykin is the aging, disillusioned army doctor whose cynicism and emotional detachment embody the themes of lost hope and stagnation in Anton Chekhov’s play "Three Sisters."
- 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: Koganov Triple: [Kogan, hasAlternativeForm, Koganov]
Generated description
Koganov is a surname, likely of Slavic or Eastern European origin, used as a variant form of the name Kogan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Koganov Target entity description: Koganov is a surname, likely of Slavic or Eastern European origin, used as a variant form of the name Kogan.
-
A.
Gryzlov
Gryzlov is a Russian surname most prominently associated with Boris Gryzlov, a notable Russian politician and former chairman of the State Duma.
-
B.
Kozlov
Kozlov is a historic Russian town, now known as Michurinsk, that developed as a significant regional center of trade and agriculture.
-
C.
Kozlov
Kozlov is the former Russian name of the city now known as Gözleve (Eupatoria) in Crimea, reflecting its historical period under Russian influence.
-
D.
Kovalyov
Kovalyov is the absurdly unfortunate civil servant protagonist of Shostakovich’s opera “The Nose,” whose detached nose gains a higher social rank than he does.
-
E.
Chebutykin
Chebutykin is the aging, disillusioned army doctor whose cynicism and emotional detachment embody the themes of lost hope and stagnation in Anton Chekhov’s play "Three Sisters."
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65867b5408190bbd12ca567c4705f |
completed | April 20, 2026, 4:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07d44098188190b2627bbf3695495d |
completed | May 16, 2026, 2:19 a.m. |
| NEDg | Description generation | batch_6a07d51bda3c81908575cd41a212c108 |
completed | May 16, 2026, 2:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07d5d7c4bc8190ab189fa556a956d7 |
completed | May 16, 2026, 2:26 a.m. |
Created at: April 10, 2026, 1:51 p.m.