Triple
T9368430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Varvara Andreevna Zmuidzinas |
E225467
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Varvara |
E41336
|
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: Varvara | Statement: [Varvara Andreevna Zmuidzinas, hasGivenName, Varvara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varvara Context triple: [Varvara Andreevna Zmuidzinas, hasGivenName, Varvara]
-
A.
Varvara
chosen
Varvara is the Slavic form of the female given name Barbara, commonly used in Russian and other Eastern European languages.
-
B.
Nadezhda
Nadezhda is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and meaning "hope."
-
C.
Vasilyeva
Vasilyeva is a common Russian surname, typically the feminine form of Vasilyev, derived from the given name Vasily.
-
D.
Praskovya
Praskovya is the given name of Pasha Angelina, a renowned Soviet female tractor driver and labor heroine.
-
E.
Vika
Vika is a central neighborhood in Oslo, Norway, known for its waterfront location, cultural institutions, and proximity to the city’s business district.
- 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_69ca842cbddc819099d71ecec48cf9e5 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd507f9ed8819092967b204faa4408 |
completed | April 1, 2026, 5:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0f40961e88190b12ab78edbebd252 |
completed | April 4, 2026, 11:20 a.m. |
Created at: March 30, 2026, 7:43 p.m.