Triple
T20076986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My Sister's Keeper |
E499892
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Cameron Diaz |
—
|
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: Cameron Diaz | Statement: [My Sister's Keeper, stars, Cameron Diaz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cameron Diaz Context triple: [My Sister's Keeper, stars, Cameron Diaz]
-
A.
Cameron Diaz
chosen
Cameron Diaz is an American actress known for her roles in hit films such as "There's Something About Mary," "Charlie's Angels," and "Shrek."
-
B.
Jessica Alba
Jessica Alba is an American actress and businesswoman known for her roles in films like "Fantastic Four" and for founding the consumer goods company The Honest Company.
-
C.
Jolie Gabor
Jolie Gabor was a Hungarian-American jeweler and socialite best known as the glamorous matriarch of the Gabor family of actresses and celebrities.
-
D.
Katherine Heigl
Katherine Heigl is an American actress and former fashion model best known for her roles in the television series "Grey's Anatomy" and various romantic comedy films.
-
E.
Jessica Biel
Jessica Biel is an American actress and producer known for her roles in the TV series "7th Heaven" and films such as "The Texas Chainsaw Massacre" and "The Illusionist."
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6643d5238819098b7d4e4e2c8dd67 |
completed | April 20, 2026, 5:37 p.m. |
Created at: April 11, 2026, 3:40 p.m.