Triple
T13126820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vasilyeva |
E311864
|
entity |
| Predicate | hasTransliteration |
P2508
|
FINISHED |
| Object | Vasilieva |
E311864
|
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: Vasilieva | Statement: [Vasilyeva, hasTransliteration, Vasilieva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vasilieva Context triple: [Vasilyeva, hasTransliteration, Vasilieva]
-
A.
Vasilyeva
chosen
Vasilyeva is a common Russian surname, typically the feminine form of Vasilyev, derived from the given name Vasily.
-
B.
Volkova
Volkova is a Russian surname commonly borne by individuals of Slavic origin, including notable figures in politics, arts, and sciences.
-
C.
Kuntsevskaya
Kuntsevskaya is a Moscow Metro station on the Big Circle Line serving the Kuntsevo District in western Moscow.
-
D.
Miloslavskaya
Miloslavskaya is a Russian surname historically associated with the noble family of Maria Miloslavskaya, the first wife of Tsar Alexei I of Russia.
-
E.
Savyolovskaya
Savyolovskaya is a Moscow Metro station on the Big Circle Line, serving as part of the city’s modern orbital rapid transit network.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9819aac388190b59bf43cc6a49d0c |
completed | April 10, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f5d59c5881909072afd0bc273f5f |
completed | May 3, 2026, 7:14 a.m. |
Created at: April 9, 2026, 9:07 p.m.