Triple
T8766419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thank You for Smoking |
E208349
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Maria Bello |
E403767
|
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: Maria Bello | Statement: [Thank You for Smoking, castMember, Maria Bello]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Bello Context triple: [Thank You for Smoking, castMember, Maria Bello]
-
A.
Maria Bello
chosen
Maria Bello is an American actress known for her versatile roles in film and television, including performances in projects like "A History of Violence," "ER," and "NCIS."
-
B.
Samantha Morton
Samantha Morton is an acclaimed English actress and director known for her intense, emotionally rich performances in independent films and major productions alike.
-
C.
Ramona Sarsgaard
Ramona Sarsgaard is the daughter of American actor Peter Sarsgaard and actress Maggie Gyllenhaal.
-
D.
Meg Tilly
Meg Tilly is a Canadian-American actress and novelist best known for her Academy Award–nominated performance in the film "Agnes of God."
-
E.
Elizabeth Perkins
Elizabeth Perkins is an American actress known for her versatile film and television roles, including work in both live-action and animated 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_69ca835df7e08190ac875664cca8f9ca |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5ee97fd0819087ef8fe14b37ae43 |
completed | March 31, 2026, 11:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf88e892688190ac1434598b3984b9 |
completed | April 3, 2026, 9:31 a.m. |
Created at: March 30, 2026, 6:41 p.m.