Triple
T17714978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pam & Tommy |
E442171
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Lily James |
—
|
NE NERFINISHED |
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: Lily James | Statement: [Pam & Tommy, starring, Lily James]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lily James Context triple: [Pam & Tommy, starring, Lily James]
-
A.
Lily James
chosen
Lily James is an English actress known for her roles in films such as Cinderella, Baby Driver, and Mamma Mia! Here We Go Again, as well as the TV series Downton Abbey.
-
B.
Tamsin Egerton
Tamsin Egerton is an English actress and model known for roles in films such as "St Trinian's," "Keeping Mum," and "The Look of Love."
-
C.
Georgie Henley
Georgie Henley is an English actress best known for playing Lucy Pevensie in the film adaptations of C.S. Lewis's "The Chronicles of Narnia" series.
-
D.
Emma Corrin
Emma Corrin is an English actor best known for their acclaimed portrayal of Princess Diana in the television series "The Crown."
-
E.
Lily Collins
Lily Collins is a British-American actress and model known for roles in films like "Mirror Mirror" and the series "Emily in Paris."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4747f217081909010f396caaf03be |
completed | April 19, 2026, 6:21 a.m. |
Created at: April 10, 2026, 10:06 a.m.