Triple
T8577974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Dawson |
E203094
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Diana Dors |
E603736
|
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: Diana Dors | Statement: [Richard Dawson, spouse, Diana Dors]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diana Dors Context triple: [Richard Dawson, spouse, Diana Dors]
-
A.
Diana Dors
chosen
Diana Dors was a British actress and sex symbol of the 1950s and 1960s, known for her glamorous image and roles in film and television.
-
B.
Sylvia Syms
Sylvia Syms was a distinguished British actress known for her extensive film, television, and stage career spanning over six decades, including prominent roles in classic British cinema.
-
C.
Alexandra Maria Lara
Alexandra Maria Lara is a Romanian-German actress known for her roles in acclaimed films such as "Downfall," "Control," and "Rush."
-
D.
Debra Paget
Debra Paget is an American actress best known for her roles in 1950s Hollywood epics and adventure films, including prominent performances in movies like "The Ten Commandments" and "Love Me Tender."
-
E.
Joan Sims
Joan Sims was a prolific English comedy actress best known for her roles in the "Carry On" film series and numerous British television and stage productions.
- 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_69ca8328ebe481909a8c038fa79959b4 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea989bec81909b8c8b4af7c568ff |
completed | March 31, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cebb8e8b9481908f7096acefaa0ffd |
completed | April 2, 2026, 6:55 p.m. |
Created at: March 30, 2026, 6:22 p.m.