Triple
T1012656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiunguja |
E21856
|
entity |
| Predicate | closelyRelatedTo |
P37
|
FINISHED |
| Object | Kimvita |
E22244
|
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: Kimvita | Statement: [Kiunguja, closelyRelatedTo, Kimvita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kimvita Context triple: [Kiunguja, closelyRelatedTo, Kimvita]
-
A.
Kimvita
chosen
Kimvita is a major coastal dialect of Swahili spoken primarily in and around Mombasa, Kenya.
-
B.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
-
C.
Kykuit
Kykuit is a historic Rockefeller family estate and grand mansion known for its architecture, art collections, and landscaped gardens overlooking the Hudson River in New York.
-
D.
Khoni
Khoni is a small town in western Georgia’s Imereti region, known for its historical churches and surrounding natural landscapes.
-
E.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
- 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_69a493c68e24819080ed0ee8bcfd5ce0 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7a8b254819089ffed9cb62a6930 |
completed | March 1, 2026, 10:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bad654c81909dd59211fafa8b2c |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:41 p.m.