Triple
T7818458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyudmila Shkrebneva |
E181069
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Shkrebneva |
E181069
|
NE FINISHED |
How this triple was built (2 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: Shkrebneva | Statement: [Lyudmila Shkrebneva, familyName, Shkrebneva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shkrebneva Context triple: [Lyudmila Shkrebneva, familyName, Shkrebneva]
-
A.
Shkrebneva
chosen
Shkrebneva is the maiden surname of Lyudmila Putina, the former wife of Russian president Vladimir Putin.
-
B.
Bashkirova
Bashkirova is a Russian-language surname commonly associated with individuals of Slavic origin.
-
C.
Govardeyskaya
Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
-
D.
Sokolovskaya
Sokolovskaya is a Russian-language surname of Slavic origin, borne by various individuals from Russian-speaking regions.
-
E.
Kuntsevskaya
Kuntsevskaya is a Moscow Metro station on the Big Circle Line serving the Kuntsevo District in western Moscow.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf9708bdc8190a5154efe0f96f458 |
completed | March 30, 2026, 10:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5a5c24908190847b612a56a1abf5 |
completed | March 31, 2026, 5:23 a.m. |
Created at: March 30, 2026, 4:40 p.m.