Triple
T10285564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilkes |
E241217
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Wilke |
E619108
|
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: Wilke | Statement: [Wilkes, hasVariant, Wilke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wilke Context triple: [Wilkes, hasVariant, Wilke]
-
A.
Wilke
chosen
Wilke is a German-origin surname that serves as the root form for related family names such as Wilkens.
-
B.
Wiebe
Wiebe is a given name and surname of Frisian and Dutch origin, used in various forms across the Netherlands and surrounding regions.
-
C.
Wilsen
Wilsen is a variant form of the given name Wilson, used as a personal name or surname.
-
D.
Wilkin
Wilkin is a medieval English given name that originated as a diminutive form of William and later gave rise to the surname Wilkinson.
-
E.
Weigel
Weigel is a German-language surname borne by various notable figures in fields such as science, the arts, and public life.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b737788190bfadd0d48ad38f5b |
completed | April 7, 2026, 9:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f8444c48819095100c6d1d45ccc7 |
completed | April 9, 2026, 12:52 a.m. |
Created at: April 6, 2026, 11:40 a.m.