Triple
T9984149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mykelti Williamson |
E196523
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Donna Ramsey |
E196523
|
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: Donna Ramsey | Statement: [Mykelti Williamson, spouse, Donna Ramsey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donna Ramsey Context triple: [Mykelti Williamson, spouse, Donna Ramsey]
-
A.
Donna Ramsey
chosen
Donna Ramsey is known as the spouse of American actor Mykelti Williamson, recognized for his roles in films like "Forrest Gump" and various television series.
-
B.
Donna Weiss
Donna Weiss is an American songwriter best known for co-writing the hit song "Bette Davis Eyes."
-
C.
Beverly Todd
Beverly Todd is an American actress known for her work in film, television, and theater, including a notable role in the comedy-drama "The Bucket List."
-
D.
Donna Moss
Donna Moss is a key fictional character on the television series "The West Wing," known for her role as Josh Lyman’s witty and capable assistant who evolves into a significant political operative.
-
E.
Suzanne Todd
Suzanne Todd is an American film producer known for her work on influential movies such as "Memento" and the "Austin Powers" series.
- 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_69ca82efbce081908179b4b9c65096eb |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb8bdc0388190bbbd4bdc5ac3adec |
completed | April 2, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d257fe0e348190b55fbd38e21cff7c |
completed | April 5, 2026, 12:39 p.m. |
Created at: March 30, 2026, 8:49 p.m.