Triple
T10457886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Last Christmas |
E246592
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Emma Thompson |
E3055
|
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: Emma Thompson | Statement: [Last Christmas, starring, Emma Thompson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emma Thompson Context triple: [Last Christmas, starring, Emma Thompson]
-
A.
Emma Thompson
chosen
Emma Thompson is an acclaimed British actress and screenwriter known for her Oscar-winning performances and adaptations in films such as "Howards End" and "Sense and Sensibility."
-
B.
Joanna Lumley
Joanna Lumley is a British actress, presenter, and former model best known for her iconic role as Patsy Stone in the television series "Absolutely Fabulous."
-
C.
Dawn French
Dawn French is a British comedian and actress best known as one half of the comedy duo French and Saunders and for her acclaimed television work in shows such as "The Vicar of Dibley."
-
D.
Cheryl Hines
Cheryl Hines is an American actress and director best known for her role as Larry David’s wife, Cheryl, on the HBO series "Curb Your Enthusiasm."
-
E.
Betsy Aidem
Betsy Aidem is an American actress known for her work in film, television, and theater.
- 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_69d4fe4a56e08190ab56d762d6a91b01 |
completed | April 7, 2026, 12:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89fbf3a308190af6b605ce781396a |
completed | April 10, 2026, 6:59 a.m. |
Created at: April 6, 2026, 12:18 p.m.