Triple
T20076807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheila Garrett |
E499888
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Henry Wilcoxon |
—
|
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: Henry Wilcoxon | Statement: [Sheila Garrett, spouse, Henry Wilcoxon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Henry Wilcoxon Context triple: [Sheila Garrett, spouse, Henry Wilcoxon]
-
A.
Henry Wilcoxon
chosen
Henry Wilcoxon was a British actor best known for his leading roles in 1930s and 1940s Hollywood epics and for his frequent collaborations with director Cecil B. DeMille.
-
B.
William Kruskal
William Kruskal was an American statistician best known for co-developing the Kruskal–Wallis test, a nonparametric method for comparing multiple groups.
-
C.
Egon Pearson
Egon Pearson was a British statistician best known for co-developing the Neyman–Pearson lemma, a fundamental result in hypothesis testing.
-
D.
C. B. Cochran
C. B. Cochran was a prominent British theatrical impresario and producer known for staging lavish musical revues and plays in the early 20th century.
-
E.
Samuel Wilks
Samuel Wilks was an influential American statistician known for his foundational contributions to mathematical statistics and its applications during the mid-20th century.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6643bcfd48190893abd3734f15cd3 |
completed | April 20, 2026, 5:37 p.m. |
Created at: April 11, 2026, 3:40 p.m.