Triple
T10646858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | De Witt |
E250857
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | DeWit |
E878181
|
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: DeWit | Statement: [De Witt, hasVariant, DeWit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DeWit Context triple: [De Witt, hasVariant, DeWit]
-
A.
DeWit
chosen
DeWit is a surname of Dutch origin, commonly appearing as a variant of "De Wit."
-
B.
DeWint
DeWint is a family name most notably associated with the English watercolour painter Peter De Wint and his artistic descendants.
-
C.
Diemaco
Diemaco is a Canadian firearms manufacturer best known for producing and developing variants of the AR-15/M16 family of rifles for military and law enforcement use.
-
D.
Nortrup
Nortrup is a small municipality in Lower Saxony, Germany, situated within the Artland region.
-
E.
Dellner
Dellner is a company specializing in railway coupling and connection systems used on modern passenger and freight trains worldwide.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfe1cd6081909df9e4dc0fda1f0b |
completed | April 8, 2026, 11:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d988530f288190b8150d159f723a74 |
completed | April 10, 2026, 11:31 p.m. |
Created at: April 8, 2026, 9:05 p.m.