Triple
T21946395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikki |
E541943
|
entity |
| Predicate | portrayedInFilmBy |
P9616
|
FINISHED |
| Object | Brea Bee |
—
|
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: Brea Bee | Statement: [Nikki, portrayedInFilmBy, Brea Bee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brea Bee Context triple: [Nikki, portrayedInFilmBy, Brea Bee]
-
A.
Brea Bee
chosen
Brea Bee is an American actress best known for her supporting role in the film "Silver Linings Playbook."
-
B.
Brea
Brea is the protagonist of the 2018 thriller film "Traffik," a woman who becomes entangled in a dangerous human-trafficking ring during a romantic getaway.
-
C.
Beeban
Beeban is a feminine given name most notably borne by British film director Beeban Kidron.
-
D.
Bonita
Bonita is a suburban community in southern San Diego County, California, known for its residential neighborhoods, golf courses, and proximity to the Sweetwater River.
-
E.
Lymon
Lymon is a variant spelling of the given name and surname Lyman, used for people and occasionally fictional characters.
- 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12427c2b48190949c41bd3be2d9f3 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:57 p.m.