Triple
T18605778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corne |
E454741
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Korne |
—
|
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: Korne | Statement: [Corne, hasVariant, Korne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Korne Context triple: [Corne, hasVariant, Korne]
-
A.
Korne
chosen
Korne is a river in the Netherlands on which the town of Buren is situated.
-
B.
Kropinski
Kropinski is a surname most notably associated with South African-born actress Kasha Kropinski.
-
C.
Krewo
Krewo is a historic village in present-day Belarus, best known as the site where the Union of Krewo was concluded in 1385, marking a pivotal dynastic union between the Kingdom of Poland and the Grand Duchy of Lithuania.
-
D.
Kohner
Kohner is a surname most notably associated with American actress Susan Kohner, known for her acclaimed film and television work in the mid-20th century.
-
E.
Korenlei
Korenlei is a historic quay along the Leie River in Ghent, Belgium, known for its picturesque medieval guild houses and waterfront views.
- 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e547544a248190a3465e22dfb29305 |
completed | April 19, 2026, 9:21 p.m. |
Created at: April 10, 2026, 11:45 a.m.