Triple
T3433647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Winslet |
E72394
|
entity |
| Predicate | parent |
P120
|
FINISHED |
| Object |
Sally Bridges-Winslet
Sally Bridges-Winslet is the daughter of English actress Kate Winslet.
|
E372265
|
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: Sally Bridges-Winslet | Statement: [Kate Winslet, parent, Sally Bridges-Winslet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sally Bridges-Winslet Context triple: [Kate Winslet, parent, Sally Bridges-Winslet]
-
A.
Beth Winslet
Beth Winslet is a British actress and the younger sister of acclaimed film star Kate Winslet.
-
B.
Joss Winslet
Joss Winslet is a sibling of acclaimed English actress Kate Winslet and a member of the Winslet family connected to the entertainment industry.
-
C.
Anna Winslet
Anna Winslet is a member of the Winslet family and the sister of acclaimed English actress Kate Winslet.
-
D.
Kate Winslet
Kate Winslet is an acclaimed English actress known for her versatile performances in films such as "Titanic," "Eternal Sunshine of the Spotless Mind," and "The Reader," for which she has received numerous major awards.
-
E.
Michelle Dockery
Michelle Dockery is an English actress best known for her role as Lady Mary Crawley in the television series "Downton Abbey."
- 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: Sally Bridges-Winslet Triple: [Kate Winslet, parent, Sally Bridges-Winslet]
Generated description
Sally Bridges-Winslet is the daughter of English actress Kate Winslet.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sally Bridges-Winslet Target entity description: Sally Bridges-Winslet is the daughter of English actress Kate Winslet.
-
A.
Beth Winslet
Beth Winslet is a British actress and the younger sister of acclaimed film star Kate Winslet.
-
B.
Joss Winslet
Joss Winslet is a sibling of acclaimed English actress Kate Winslet and a member of the Winslet family connected to the entertainment industry.
-
C.
Anna Winslet
Anna Winslet is a member of the Winslet family and the sister of acclaimed English actress Kate Winslet.
-
D.
Kate Winslet
Kate Winslet is an acclaimed English actress known for her versatile performances in films such as "Titanic," "Eternal Sunshine of the Spotless Mind," and "The Reader," for which she has received numerous major awards.
-
E.
Michelle Dockery
Michelle Dockery is an English actress best known for her role as Lady Mary Crawley in the television series "Downton Abbey."
- 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_69ad85af50288190a854b76653deee6f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9c1d9148190b873ba66d34d4f01 |
completed | March 8, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b402c6e5bc819099a5148ad509b22d |
completed | March 13, 2026, 12:27 p.m. |
| NEDg | Description generation | batch_69b40335a05c8190b51414f284bd6429 |
completed | March 13, 2026, 12:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b40a6bd4888190a26989e5f6770e2c |
completed | March 13, 2026, 1 p.m. |
Created at: March 8, 2026, 3:16 p.m.