Triple
T18508881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Becca Nolan |
E452277
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Makenna James |
—
|
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: Makenna James | Statement: [Becca Nolan, portrayedBy, Makenna James]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Makenna James Context triple: [Becca Nolan, portrayedBy, Makenna James]
-
A.
Makenna James
chosen
Makenna James is an American actress best known for her role on the television series "American Woman."
-
B.
Makenna Allen
Makenna Allen is known as the sister of NFL quarterback Josh Allen.
-
C.
Mackenzie Mauzy
Mackenzie Mauzy is an American actress and singer known for her work on Broadway and in film and television, including her role as Rapunzel in the 2014 musical fantasy film "Into the Woods."
-
D.
Makayla Epps
Makayla Epps is an American basketball player best known for her standout collegiate career as a guard for the University of Kentucky women's basketball team.
-
E.
Makenzie Moss
Makenzie Moss is an American actress known for her roles as a child performer in films and television, including a part in the biographical drama "Steve Jobs" (2015).
- 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_69d8d386df84819092355ebb260d848e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53344c6b081908e780ed5c815a766 |
completed | April 19, 2026, 7:55 p.m. |
Created at: April 10, 2026, 11:36 a.m.