Triple
T10452628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Woman Who Cooked Her Husband |
E246467
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Debbie Isitt |
E863417
|
NE FINISHED |
How this triple was built (2 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: Debbie Isitt | Statement: [The Woman Who Cooked Her Husband, writer, Debbie Isitt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Debbie Isitt Context triple: [The Woman Who Cooked Her Husband, writer, Debbie Isitt]
-
A.
Debbie Isitt
chosen
Debbie Isitt is a British writer and director best known for her dark comedies and for creating the popular "Nativity!" film series.
-
B.
Susan Ekins
Susan Ekins is a film producer best known for her work on major Hollywood projects, including the heist comedy "Ocean's 8."
-
C.
Gillian Siddall
Gillian Siddall is a Canadian academic and university administrator who serves as president of Lakehead University.
-
D.
Denise Miller
Denise Miller is an American actress best known for her television work in the late 1970s and early 1980s, including prominent roles in sitcoms.
-
E.
Krysty Wilson-Cairns
Krysty Wilson-Cairns is a Scottish screenwriter known for co-writing the acclaimed World War I film "1917" and working on various high-profile film and television projects.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe0b7bb481908182c7b9a80af3b3 |
completed | April 7, 2026, 12:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89fb27f5081909e78bd8029e65948 |
completed | April 10, 2026, 6:58 a.m. |
Created at: April 6, 2026, 12:17 p.m.