Triple
T5264163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dina |
E118897
|
entity |
| Predicate | hasTransliteration |
P2508
|
FINISHED |
| Object | Дина |
E118897
|
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: Дина | Statement: [Dina, hasTransliteration, Дина]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Дина Context triple: [Dina, hasTransliteration, Дина]
-
A.
Dina
chosen
Dina is a feminine given name used in various cultures, often as a variant of names like Dinah or Edina.
-
B.
Arapova
Arapova is a Russian-language surname historically borne by various individuals of Slavic origin.
-
C.
Tamina
The Tamina is a river in eastern Switzerland known for flowing through the deep Tamina Gorge before joining the Alpine Rhine.
-
D.
Larisa
Larisa is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
-
E.
Larisa
Larisa was an ancient Greek city located in the region of Aeolis in western Asia Minor.
- 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bd4a9888190a79ef8e64c764f86 |
completed | March 20, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf06c71d308190a42a2da51b4cf93e |
completed | March 21, 2026, 8:59 p.m. |
Created at: March 20, 2026, 1:51 p.m.