Triple
T19628831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Cookout |
E471210
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Meagan Good |
—
|
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: Meagan Good | Statement: [The Cookout, stars, Meagan Good]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meagan Good Context triple: [The Cookout, stars, Meagan Good]
-
A.
Meagan Good
chosen
Meagan Good is an American actress known for her work in film and television, particularly in romantic comedies and dramas.
-
B.
Melonie Diaz
Melonie Diaz is an American actress known for her work in independent films and television, including prominent roles in projects like "Fruitvale Station" and the "Charmed" reboot.
-
C.
Deva Cassel
Deva Cassel is an Italian model and emerging actress, known as the daughter of Monica Bellucci and Vincent Cassel.
-
D.
Lauren Boyle
Lauren Boyle is a New Zealand freestyle swimmer and multiple World Championship medallist known for her success in middle- and long-distance events.
-
E.
Yeardley Smith
Yeardley Smith is an American actress and voice actress best known for voicing Lisa Simpson on the long-running animated television series "The Simpsons."
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641007e5881908da78e50aa36f340 |
completed | April 20, 2026, 3:06 p.m. |
Created at: April 10, 2026, 1:44 p.m.