Triple
T20063233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Lapaine |
E499536
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Fay Ripley
Fay Ripley is an English actress and cookery writer best known for her role in the television drama series "Cold Feet."
|
E1409961
|
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: Fay Ripley | Statement: [Daniel Lapaine, spouse, Fay Ripley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fay Ripley Context triple: [Daniel Lapaine, spouse, Fay Ripley]
-
A.
Faye Medwick
Faye Medwick is a fictional character appearing in the work titled "Chapter Two."
-
B.
Peg Fenwick
Peg Fenwick was an American screenwriter best known for her work on mid-20th-century Hollywood melodramas.
-
C.
Fay Holden
Fay Holden was a British-born American actress best known for playing Mrs. Emily Hardy, the mother in the popular Andy Hardy film series of the 1930s and 1940s.
-
D.
Fay Compton
Fay Compton was a prominent English stage and film actress of the early to mid-20th century, renowned for her Shakespearean roles and appearances in classic British cinema.
-
E.
Joan Winfield
Joan Winfield is a fictional heiress character in the 1941 romantic comedy film "The Bride Came C.O.D.," portrayed by actress Bette Davis.
- 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: Fay Ripley Triple: [Daniel Lapaine, spouse, Fay Ripley]
Generated description
Fay Ripley is an English actress and cookery writer best known for her role in the television drama series "Cold Feet."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fay Ripley Target entity description: Fay Ripley is an English actress and cookery writer best known for her role in the television drama series "Cold Feet."
-
A.
Faye Medwick
Faye Medwick is a fictional character appearing in the work titled "Chapter Two."
-
B.
Peg Fenwick
Peg Fenwick was an American screenwriter best known for her work on mid-20th-century Hollywood melodramas.
-
C.
Fay Holden
Fay Holden was a British-born American actress best known for playing Mrs. Emily Hardy, the mother in the popular Andy Hardy film series of the 1930s and 1940s.
-
D.
Fay Compton
Fay Compton was a prominent English stage and film actress of the early to mid-20th century, renowned for her Shakespearean roles and appearances in classic British cinema.
-
E.
Joan Winfield
Joan Winfield is a fictional heiress character in the 1941 romantic comedy film "The Bride Came C.O.D.," portrayed by actress Bette Davis.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66377b6b48190a0a37279f285123e |
completed | April 20, 2026, 5:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a081f33d7808190b71c69701fc85a02 |
completed | May 16, 2026, 7:39 a.m. |
| NEDg | Description generation | batch_6a0820d8d2c48190b8c75fc59e43462a |
completed | May 16, 2026, 7:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08212942e88190a385e094a27b3ede |
completed | May 16, 2026, 7:47 a.m. |
Created at: April 11, 2026, 3:39 p.m.