Triple
T22798056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Water High |
E564302
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Kate 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: Kate Bell | Statement: [Blue Water High, stars, Kate Bell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kate Bell Context triple: [Blue Water High, stars, Kate Bell]
-
A.
Kate Bell
chosen
Kate Bell is an Australian actress best known for her role in the psychological drama film "In Her Skin."
-
B.
Cassandra Harris
Cassandra Harris was an Australian actress and Bond girl best known for her role in "For Your Eyes Only" and for being the first wife of actor Pierce Brosnan.
-
C.
Amelia Crouch
Amelia Crouch is a British actress known for her roles as a child and young teen in horror and fantasy films and television series.
-
D.
Katie Bell Nubin
Katie Bell Nubin was a gospel singer and evangelist known for nurturing her daughter Sister Rosetta Tharpe’s musical and spiritual development.
-
E.
Bella O’Reilly
Bella O’Reilly is a central fictional character in the crime drama film "Widows," involved in a high-stakes heist after her partner’s death.
- 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_69e2458185f88190b0045227ee420411 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17cda76448190891c5190e1d75ae0 |
completed | April 29, 2026, 3:36 a.m. |
Created at: April 17, 2026, 3:30 p.m.