Triple
T19612469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | So Weird |
E470766
|
entity |
| Predicate | characterPortrayed |
P1507
|
FINISHED |
| Object | Carey Bell |
—
|
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: Carey Bell | Statement: [So Weird, characterPortrayed, Carey Bell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carey Bell Context triple: [So Weird, characterPortrayed, Carey Bell]
-
A.
Carey Bell
Carey Bell is an American clarinetist best known as the principal clarinet of the San Francisco Symphony.
-
B.
Carey Bell
chosen
Carey Bell is a fictional character from the Disney Channel series "So Weird," known as a member of the touring music family around whom the show's supernatural adventures unfold.
-
C.
Carey Mahoney
Carey Mahoney is the wisecracking, rebellious police recruit and central protagonist of the early Police Academy comedy films.
-
D.
Lisa Conroy
Lisa Conroy is the hardworking, empathetic general manager of a roadside sports bar who struggles to protect and support her staff amid personal and professional turmoil in the film "Support the Girls."
-
E.
April Sexton
April Sexton is a dedicated emergency department nurse and central character in the medical drama series "Chicago Med."
- 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_69d8e510fa248190b7afb274a1d4cf73 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640cbeda08190addb1adf84af4993 |
completed | April 20, 2026, 3:05 p.m. |
Created at: April 10, 2026, 1:43 p.m.