Triple
T14990416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | From Prada to Nada |
E373819
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Fannon Rogers
Fannon Rogers is a film producer best known for his work on the romantic comedy "From Prada to Nada."
|
E1219894
|
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: Fannon Rogers | Statement: [From Prada to Nada, producer, Fannon Rogers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fannon Rogers Context triple: [From Prada to Nada, producer, Fannon Rogers]
-
A.
Vivian Bonnell
Vivian Bonnell was an actress known for her work in film and television, including a role in the biographical drama "The Josephine Baker Story."
-
B.
Eileen Morrow
Eileen Morrow is a person notable enough to be recognized as a significant bearer of the surname Morrow.
-
C.
Eileen Fulton
Eileen Fulton is an American actress best known for originating and playing the iconic character Lisa Grimaldi on the long-running soap opera "As the World Turns" for several decades.
-
D.
Eileen Shearer
Eileen Shearer is a political figure best known for founding the American Independent Party in the United States.
-
E.
Frances Brundage
Frances Brundage was an American illustrator best known for her sentimental and richly detailed depictions of children on postcards and in books during the late 19th and early 20th centuries.
- 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: Fannon Rogers Triple: [From Prada to Nada, producer, Fannon Rogers]
Generated description
Fannon Rogers is a film producer best known for his work on the romantic comedy "From Prada to Nada."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fannon Rogers Target entity description: Fannon Rogers is a film producer best known for his work on the romantic comedy "From Prada to Nada."
-
A.
Vivian Bonnell
Vivian Bonnell was an actress known for her work in film and television, including a role in the biographical drama "The Josephine Baker Story."
-
B.
Eileen Morrow
Eileen Morrow is a person notable enough to be recognized as a significant bearer of the surname Morrow.
-
C.
Eileen Fulton
Eileen Fulton is an American actress best known for originating and playing the iconic character Lisa Grimaldi on the long-running soap opera "As the World Turns" for several decades.
-
D.
Eileen Shearer
Eileen Shearer is a political figure best known for founding the American Independent Party in the United States.
-
E.
Frances Brundage
Frances Brundage was an American illustrator best known for her sentimental and richly detailed depictions of children on postcards and in books during the late 19th and early 20th centuries.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7148a308190a687f4d0d61397c6 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00679214208190a9ee4cce882f59cb |
completed | May 10, 2026, 11:10 a.m. |
| NEDg | Description generation | batch_6a006895b8ac8190a8d078e6b9f5bb50 |
completed | May 10, 2026, 11:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00694da4a88190944ae4a70ac9f0c3 |
completed | May 10, 2026, 11:17 a.m. |
Created at: April 10, 2026, 2:53 a.m.