Triple
T7288297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In Too Deep |
E163929
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Pam Grier |
E65189
|
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: Pam Grier | Statement: [In Too Deep, castMember, Pam Grier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pam Grier Context triple: [In Too Deep, castMember, Pam Grier]
-
A.
Pam Grier
chosen
Pam Grier is an iconic American actress best known for her groundbreaking roles in 1970s blaxploitation films such as "Coffy" and "Foxy Brown," which established her as a pioneering Black female action star.
-
B.
Donna Peele
Donna Peele is an American former model best known for her brief mid-1990s marriage to actor Charlie Sheen.
-
C.
Madolyn Smith
Madolyn Smith is an American actress best known for her film and television roles in the 1980s, including prominent performances in comedies and dramas.
-
D.
Madolyn Madden
Madolyn Madden is a central character in the crime thriller film "The Departed," serving as a psychiatrist entangled in the lives of both a mole in the police and an undercover cop.
-
E.
Patty Fenn
Patty Fenn is a television producer and key character in the film "Money Monster," where she manages the chaotic live broadcast at the center of the story.
- 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_69c6886093b88190a254b1ce6db8bae7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb6a73fc8190ae5ce81fd3e46d87 |
completed | March 27, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db4671e08190874d5e099e883509 |
completed | March 28, 2026, 1:44 p.m. |
Created at: March 27, 2026, 2:59 p.m.