Triple
T4857706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aleksandra Dulkiewicz |
E108576
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Aleksandra |
E260502
|
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: Aleksandra | Statement: [Aleksandra Dulkiewicz, givenName, Aleksandra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aleksandra Context triple: [Aleksandra Dulkiewicz, givenName, Aleksandra]
-
A.
Aleksandra
chosen
Aleksandra is a feminine given name of Slavic origin, commonly used in various Eastern and Central European countries.
-
B.
Svetlana
Svetlana is a feminine given name of Slavic origin, most notably borne by Svetlana Alliluyeva, the daughter of Soviet leader Joseph Stalin.
-
C.
Yulia
Yulia is a feminine given name, commonly used in Slavic countries as a form of the name Julia.
-
D.
Galina
Galina is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
-
E.
Lyudmila
Lyudmila is a Russian linguist and the former First Lady of Russia, known for being the ex-wife of President Vladimir Putin.
- 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d3f24688190b2f2b79bcde96973 |
completed | March 20, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be5cf05d7c8190ac6e1b9e93b5256f |
completed | March 21, 2026, 8:55 a.m. |
Created at: March 20, 2026, 1:26 p.m.