Triple
T20076808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Wilcoxon |
E499888
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Sheila Garrett |
—
|
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: Sheila Garrett | Statement: [Henry Wilcoxon, spouse, Sheila Garrett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sheila Garrett Context triple: [Henry Wilcoxon, spouse, Sheila Garrett]
-
A.
Sheila Garrett
chosen
Sheila Garrett was the wife of British actor Henry Wilcoxon, known for her long marriage to the prominent film and television performer.
-
B.
Rebecca Luker
Rebecca Luker was a celebrated American Broadway soprano and actress known for her luminous performances in classic musicals such as The Secret Garden, Show Boat, and The Music Man.
-
C.
Diane Lester
Diane Lester is a key character in the financial thriller film "Money Monster," serving as a corporate communications chief entangled in the unfolding live-broadcast crisis.
-
D.
Lisa Sheridan
Lisa Sheridan is the troubled protagonist of the psychological thriller film "Obsessed," whose fixation drives the story's escalating tension and conflict.
-
E.
Lisa Sheridan
Lisa Sheridan is an American actress best known for her roles on television series such as "Invasion," "FreakyLinks," and "Halt and Catch Fire."
- 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.