Triple
T4441035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kindergarten Cop |
E95770
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Penelope Ann Miller |
E322154
|
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: Penelope Ann Miller | Statement: [Kindergarten Cop, starring, Penelope Ann Miller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penelope Ann Miller Context triple: [Kindergarten Cop, starring, Penelope Ann Miller]
-
A.
Penelope Ann Miller
chosen
Penelope Ann Miller is an American actress known for her roles in films such as "Carlito's Way," "The Artist," and "Kindergarten Cop."
-
B.
Melissa George
Melissa George is an Australian actress known for her roles in both film and television, including prominent performances in horror and thriller genres.
-
C.
Maggie Siff
Maggie Siff is an American actress best known for her television roles in series such as Mad Men, Sons of Anarchy, and Billions.
-
D.
Carrie Coon
Carrie Coon is an American actress known for her acclaimed performances in television series like "The Leftovers" and "Fargo" as well as films such as "Gone Girl" and "The Nest."
-
E.
Kate Mara
Kate Mara is an American actress known for her roles in films like "The Martian" and "Brokeback Mountain" and TV series such as "House of Cards."
- 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_69b3453ea2b48190a26f154b3b8fece5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355ad71588190b1dcad4250472c29 |
completed | March 13, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6281264f08190942d2043495c89d5 |
completed | March 15, 2026, 3:31 a.m. |
Created at: March 12, 2026, 11:32 p.m.