Triple
T10108872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sergei Sazonov |
E218190
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Sazonov
Sazonov is a Russian surname most notably associated with Sergei Sazonov, the early 20th-century Russian foreign minister involved in pre–World War I diplomacy.
|
E846963
|
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: Sazonov | Statement: [Sergei Sazonov, familyName, Sazonov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sazonov Context triple: [Sergei Sazonov, familyName, Sazonov]
-
A.
Matakevich
Matakevich is a surname most notably borne by American football linebacker and special teams standout Tyler Matakevich.
-
B.
Rykov
Rykov is a Russian surname most notably associated with Alexei Rykov, a prominent early Soviet politician and premier.
-
C.
Fyodor Tolbukhin
Fyodor Tolbukhin was a prominent Soviet military commander and Marshal of the Soviet Union, noted for leading major Red Army offensives on the Eastern Front during World War II.
-
D.
Fyodor Yenakiyev
Fyodor Yenakiyev was a Russian industrialist and mining entrepreneur after whom the Ukrainian city of Yenakiieve was named.
-
E.
Tolbukhin
Tolbukhin is a Russian surname most notably associated with Soviet military commander Fyodor Tolbukhin, a prominent general during World War II.
- 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: Sazonov Triple: [Sergei Sazonov, familyName, Sazonov]
Generated description
Sazonov is a Russian surname most notably associated with Sergei Sazonov, the early 20th-century Russian foreign minister involved in pre–World War I diplomacy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sazonov Target entity description: Sazonov is a Russian surname most notably associated with Sergei Sazonov, the early 20th-century Russian foreign minister involved in pre–World War I diplomacy.
-
A.
Matakevich
Matakevich is a surname most notably borne by American football linebacker and special teams standout Tyler Matakevich.
-
B.
Rykov
Rykov is a Russian surname most notably associated with Alexei Rykov, a prominent early Soviet politician and premier.
-
C.
Fyodor Tolbukhin
Fyodor Tolbukhin was a prominent Soviet military commander and Marshal of the Soviet Union, noted for leading major Red Army offensives on the Eastern Front during World War II.
-
D.
Fyodor Yenakiyev
Fyodor Yenakiyev was a Russian industrialist and mining entrepreneur after whom the Ukrainian city of Yenakiieve was named.
-
E.
Tolbukhin
Tolbukhin is a Russian surname most notably associated with Soviet military commander Fyodor Tolbukhin, a prominent general during World War II.
- 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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd0cbd8a48190b2af6177d1249f58 |
completed | April 2, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3174bc46081909d78cdb524625ec3 |
completed | April 6, 2026, 2:15 a.m. |
| NEDg | Description generation | batch_69d3183a8410819094e81fe9f43717b2 |
completed | April 6, 2026, 2:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d318adfcb081909a3567f5327765ab |
completed | April 6, 2026, 2:21 a.m. |
Created at: March 30, 2026, 9:03 p.m.