Triple
T11416376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Livingstone |
E270500
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Joan Benny |
E342087
|
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: Joan Benny | Statement: [Mary Livingstone, child, Joan Benny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joan Benny Context triple: [Mary Livingstone, child, Joan Benny]
-
A.
Joan Benny
chosen
Joan Benny is an American actress and author best known as the daughter of legendary comedian Jack Benny and for her work preserving and chronicling his legacy.
-
B.
Joan Towne
Joan Towne was a 17th-century New England woman known primarily as the mother of Sarah Towne Cloyce, one of the women accused during the Salem witch trials.
-
C.
Joan Sands
Joan Sands was the wife of American comedian and actor Phil Silvers.
-
D.
Joan Murray
Joan Murray was the wife of famed British World War II flying ace and double amputee Sir Douglas Bader.
-
E.
Judy Bernly
Judy Bernly is a timid, recently separated office worker who becomes an unlikely feminist heroine as she joins her coworkers in overthrowing their sexist boss in the comedy film "9 to 5."
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d801ae47d0819098123505309c4a68 |
completed | April 9, 2026, 7:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e8d6392881908fd33d340f3334e7 |
completed | April 20, 2026, 8:50 a.m. |
Created at: April 8, 2026, 9:34 p.m.