Triple
T18923441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivanna Klympush-Tsintsadze |
E462918
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ivanna |
—
|
NE NERFINISHED |
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: Ivanna | Statement: [Ivanna Klympush-Tsintsadze, givenName, Ivanna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ivanna Context triple: [Ivanna Klympush-Tsintsadze, givenName, Ivanna]
-
A.
Yulia
Yulia is a feminine given name, commonly used in Slavic countries as a form of the name Julia.
-
B.
Ivanna Klympush-Tsintsadze
chosen
Ivanna Klympush-Tsintsadze is a Ukrainian politician and former vice prime minister known for overseeing European and Euro-Atlantic integration efforts in Ukraine.
-
C.
Ivanova
Ivanova is a common Slavic surname, particularly prevalent in Russia and other Eastern European countries, typically indicating female lineage from someone named Ivan.
-
D.
Zoriana Skaletska
Zoriana Skaletska is a Ukrainian lawyer and public health expert who briefly served as Ukraine’s Minister of Health in the government of Oleksiy Honcharuk.
-
E.
Ivanna Sakhno
Ivanna Sakhno is a Ukrainian-born actress known for her roles in American film and television, including prominent parts in action-comedy and science fiction projects.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c9b549448190850d7eed4de7872b |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 10, 2026, 11:59 a.m.