Triple
T7049752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sean Hepburn Ferrer |
E163733
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Karin Ferrer
Karin Ferrer is known as the wife of Sean Hepburn Ferrer, the son of actress Audrey Hepburn and actor Mel Ferrer.
|
E639410
|
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: Karin Ferrer | Statement: [Sean Hepburn Ferrer, spouse, Karin Ferrer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karin Ferrer Context triple: [Sean Hepburn Ferrer, spouse, Karin Ferrer]
-
A.
Patricia Roc
Patricia Roc was a popular British film actress of the 1940s, best known for her roles in melodramas and wartime dramas produced by major UK studios.
-
B.
Esther Ferrer
Esther Ferrer is a Spanish performance and conceptual artist known for her pioneering work in action art and minimal, often participatory installations.
-
C.
Maribel Verdú
Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
-
D.
María Elena Holly
María Elena Holly is the widow of rock and roll pioneer Buddy Holly, known for preserving and promoting his musical legacy.
-
E.
Ina Caro
Ina Caro is an American historian and travel writer known for her books that explore French history through journeys to its historic sites.
- 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: Karin Ferrer Triple: [Sean Hepburn Ferrer, spouse, Karin Ferrer]
Generated description
Karin Ferrer is known as the wife of Sean Hepburn Ferrer, the son of actress Audrey Hepburn and actor Mel Ferrer.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Karin Ferrer Target entity description: Karin Ferrer is known as the wife of Sean Hepburn Ferrer, the son of actress Audrey Hepburn and actor Mel Ferrer.
-
A.
Patricia Roc
Patricia Roc was a popular British film actress of the 1940s, best known for her roles in melodramas and wartime dramas produced by major UK studios.
-
B.
Esther Ferrer
Esther Ferrer is a Spanish performance and conceptual artist known for her pioneering work in action art and minimal, often participatory installations.
-
C.
Maribel Verdú
Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
-
D.
María Elena Holly
María Elena Holly is the widow of rock and roll pioneer Buddy Holly, known for preserving and promoting his musical legacy.
-
E.
Ina Caro
Ina Caro is an American historian and travel writer known for her books that explore French history through journeys to its historic sites.
- 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_69c6885f598c8190b6b6495c59d8d962 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e24d5e8c8190b37e56107e6da8ab |
completed | March 27, 2026, 8:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7888bba9c8190b6414b56e5588ec0 |
completed | March 28, 2026, 7:51 a.m. |
| NEDg | Description generation | batch_69c788f292a08190bf3543ecfc245d12 |
completed | March 28, 2026, 7:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c789a6ea988190ad2db2442f0a5e8f |
completed | March 28, 2026, 7:56 a.m. |
Created at: March 27, 2026, 2:37 p.m.