Triple
T22802406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forever Amber |
E564432
|
entity |
| Predicate | authorOfSourceWork |
P2353
|
FINISHED |
| Object | Kathleen Winsor |
—
|
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: Kathleen Winsor | Statement: [Forever Amber, authorOfSourceWork, Kathleen Winsor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kathleen Winsor Context triple: [Forever Amber, authorOfSourceWork, Kathleen Winsor]
-
A.
Kathleen Winsor
chosen
Kathleen Winsor was an American novelist best known for her bestselling 1944 historical romance "Forever Amber."
-
B.
Catherine Greer
Catherine Greer is a notable individual who shares the surname Greer, recognized enough to be specifically identified as a bearer of the name.
-
C.
Kathlyn Hare
Kathlyn Hare is the daring and resourceful heroine of the early 1910s adventure film serial "The Adventures of Kathlyn."
-
D.
Elinor Donahue
Elinor Donahue is an American actress best known for her work in classic television sitcoms of the 1950s and 1960s.
-
E.
Kathleen Barr
Kathleen Barr is a Canadian voice actress known for her extensive work in animation and dubbing, including numerous roles in popular children's television series and films.
- 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17cdf1e308190a05d0f61856be544 |
completed | April 29, 2026, 3:37 a.m. |
Created at: April 17, 2026, 3:31 p.m.