Triple
T11465568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ozark |
E271771
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Julia Garner |
E340704
|
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: Julia Garner | Statement: [Ozark, starring, Julia Garner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julia Garner Context triple: [Ozark, starring, Julia Garner]
-
A.
Julia Garner
chosen
Julia Garner is an American actress best known for her critically acclaimed, Emmy-winning performance as Ruth Langmore in the Netflix crime drama series "Ozark."
-
B.
Maria Riva
Maria Riva is a German-American actress and author best known as the daughter and biographer of film legend Marlene Dietrich.
-
C.
Haley Bennett
Haley Bennett is an American actress and singer known for her versatile performances in films such as "The Girl on the Train," "The Magnificent Seven," and "Swallow."
-
D.
Anya Taylor-Joy
Anya Taylor-Joy is an award-winning actress known for her breakout role in "The Queen's Gambit" and performances in films such as "The Witch," "Split," and "Last Night in Soho."
-
E.
Kaitlyn Dever
Kaitlyn Dever is an American actress known for her acclaimed performances in projects such as "Booksmart," "Short Term 12," and the miniseries "Unbelievable."
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f5eb988190b309b8e309f6d1a5 |
completed | April 9, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e684f59e2481909e96129e28c961ea |
completed | April 20, 2026, 7:56 p.m. |
Created at: April 8, 2026, 9:35 p.m.