Triple
T16986266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danielle Panabaker |
E412073
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Danielle Nicole Panabaker |
E412073
|
NE FINISHED |
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: Danielle Nicole Panabaker | Statement: [Danielle Panabaker, birthName, Danielle Nicole Panabaker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Danielle Nicole Panabaker Context triple: [Danielle Panabaker, birthName, Danielle Nicole Panabaker]
-
A.
Danielle Panabaker
chosen
Danielle Panabaker is an American actress best known for her role as Caitlin Snow/Killer Frost in the Arrowverse television series "The Flash."
-
B.
Emma Roberts
Emma Roberts is an American actress and singer known for her roles in films like "Nancy Drew" and TV series such as "American Horror Story" and "Scream Queens."
-
C.
Rachel Bilson
Rachel Bilson is an American actress best known for her television roles, including starring in the series "The O.C." and other popular TV dramas and comedies.
-
D.
Lauren Beal
Lauren Beal is an artist known for contributing creative work to the project or publication titled "Layers."
-
E.
Laura Prepon
Laura Prepon is an American actress best known for her roles on the television series That '70s Show and Orange Is the New Black.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d27b58908190a643bcbd105b1849 |
completed | April 18, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01232f69308190b4799ffcaaa98eeb |
completed | May 11, 2026, 12:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.