Triple
T14006664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roshanak |
E336966
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Roksana |
E339306
|
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: Roksana | Statement: [Roshanak, hasVariant, Roksana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roksana Context triple: [Roshanak, hasVariant, Roksana]
-
A.
Roksana
chosen
Roksana is a feminine given name, commonly used in various Slavic and Persian-influenced cultures, that is a variant of the name Roxana.
-
B.
Dagmara
Dagmara is a feminine given name, primarily used in Slavic countries, that is a variant of the name Dagmar.
-
C.
Dorota
Dorota is a feminine given name used in various Slavic and European cultures, often considered a variant of Dorothy.
-
D.
Józefina
Józefina is the Polish form of the female given name Josephine, commonly used in Poland and among Polish-speaking communities.
-
E.
Klaudia
Klaudia is the feminine given name corresponding to the male name Klaus, commonly used in various European countries.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed327d88190a53af5768468a8eb |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb653fedc81908cdd0dde2d3f3329 |
completed | May 7, 2026, 3:57 p.m. |
Created at: April 9, 2026, 10:19 p.m.