Triple
T15533989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweet Magnolias |
E370295
|
entity |
| Predicate | basedOnAuthor |
P2806
|
FINISHED |
| Object |
Sherryl Woods
Sherryl Woods is an American author best known for her popular romance and women’s fiction novels, including the "Sweet Magnolias" series that inspired the Netflix television adaptation.
|
E1162376
|
NE FINISHED |
How this triple was built (4 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: Sherryl Woods | Statement: [Sweet Magnolias, basedOnAuthor, Sherryl Woods]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sherryl Woods Context triple: [Sweet Magnolias, basedOnAuthor, Sherryl Woods]
-
A.
Shelly Johnson
Shelly Johnson is an American cinematographer known for his work on major feature films and television projects.
-
B.
Karyn Parsons
Karyn Parsons is an American actress best known for playing the snobbish yet lovable Hilary Banks on the hit 1990s sitcom "The Fresh Prince of Bel-Air."
-
C.
Lynn Weslin
Lynn Weslin is a fictional character from the baseball comedy film "Major League."
-
D.
Cheryl Crabtree Walker
Cheryl Crabtree Walker is the mother of the late American actor Paul Walker, known for his role in the "Fast & Furious" film franchise.
-
E.
Donna Dixon
Donna Dixon is an American actress and former model known for her roles in 1980s comedies and for her long career in film and television.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sherryl Woods Triple: [Sweet Magnolias, basedOnAuthor, Sherryl Woods]
Generated description
Sherryl Woods is an American author best known for her popular romance and women’s fiction novels, including the "Sweet Magnolias" series that inspired the Netflix television adaptation.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sherryl Woods Target entity description: Sherryl Woods is an American author best known for her popular romance and women’s fiction novels, including the "Sweet Magnolias" series that inspired the Netflix television adaptation.
-
A.
Shelly Johnson
Shelly Johnson is an American cinematographer known for his work on major feature films and television projects.
-
B.
Karyn Parsons
Karyn Parsons is an American actress best known for playing the snobbish yet lovable Hilary Banks on the hit 1990s sitcom "The Fresh Prince of Bel-Air."
-
C.
Lynn Weslin
Lynn Weslin is a fictional character from the baseball comedy film "Major League."
-
D.
Cheryl Crabtree Walker
Cheryl Crabtree Walker is the mother of the late American actor Paul Walker, known for his role in the "Fast & Furious" film franchise.
-
E.
Donna Dixon
Donna Dixon is an American actress and former model known for her roles in 1980s comedies and for her long career in film and television.
- F. None of above. chosen
Provenance (5 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0414877d88190804ee76566004e13 |
completed | April 16, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d605b908190a18c63142c8bb854 |
completed | May 9, 2026, 1:57 p.m. |
| NEDg | Description generation | batch_69ff3f59213c8190a9c98350225b5151 |
completed | May 9, 2026, 2:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff3ff96a6c8190a4c9f20dabc86cef |
completed | May 9, 2026, 2:08 p.m. |
Created at: April 10, 2026, 4:06 a.m.