Triple
T7133238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonard Randolph Wilkens |
E166241
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wilkens |
E155789
|
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: Wilkens | Statement: [Leonard Randolph Wilkens, familyName, Wilkens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wilkens Context triple: [Leonard Randolph Wilkens, familyName, Wilkens]
-
A.
Wilkens
chosen
Wilkens is the surname of Lenny Wilkens, a Hall of Fame American basketball player and coach.
-
B.
Wilke
Wilke is a German-origin surname that serves as the root form for related family names such as Wilkens.
-
C.
Wilkin
Wilkin is a medieval English given name that originated as a diminutive form of William and later gave rise to the surname Wilkinson.
-
D.
Willson
Willson is a less common spelling variant of the surname Wilson, typically used as a family name or occasionally as a given name.
-
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_69c68884a9388190af42f90d1c1a7151 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e6703ad88190a498665500fee5a1 |
completed | March 27, 2026, 8:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a341ede88190b43f26f1dad7bf70 |
completed | March 28, 2026, 9:45 a.m. |
Created at: March 27, 2026, 2:45 p.m.