Triple
T18440401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sydney Sweeney |
E450511
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sydney Sweeney |
—
|
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: Sydney Sweeney | Statement: [Sydney Sweeney, name, Sydney Sweeney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sydney Sweeney Context triple: [Sydney Sweeney, name, Sydney Sweeney]
-
A.
Sydney Sweeney
chosen
Sydney Sweeney is an American actress known for her breakout role as Cassie Howard in the HBO drama series "Euphoria" and for her work in both television and film.
-
B.
Natalia Dyer
Natalia Dyer is an American actress best known for her role as Nancy Wheeler in the Netflix science fiction-horror series "Stranger Things."
-
C.
Hunter Schafer
Hunter Schafer is an American model, actress, and LGBTQ+ activist best known for her breakout role as Jules Vaughn in the HBO series "Euphoria."
-
D.
Samara Weaving
Samara Weaving is an Australian actress known for her roles in film and television, particularly in horror-comedy and thriller projects such as "Ready or Not" and "The Babysitter."
-
E.
Natalie Bridges
Natalie Bridges is the wife of New Zealand politician and former National Party leader Simon Bridges.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c0fda908190901a108fb9982a2d |
completed | April 19, 2026, 6:16 p.m. |
Created at: April 10, 2026, 11:30 a.m.