Triple
T8395593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Furiosa: A Mad Max Saga |
E198044
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Anya Taylor-Joy |
E79235
|
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: Anya Taylor-Joy | Statement: [Furiosa: A Mad Max Saga, stars, Anya Taylor-Joy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anya Taylor-Joy Context triple: [Furiosa: A Mad Max Saga, stars, Anya Taylor-Joy]
-
A.
Anya Taylor-Joy
chosen
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."
-
B.
Katherine Langford
Katherine Langford is an Australian actress best known for her breakout role in the Netflix series "13 Reasons Why" and subsequent work in film and television.
-
C.
Maria Riva
Maria Riva is a German-American actress and author best known as the daughter and biographer of film legend Marlene Dietrich.
-
D.
Joey King
Joey King is an American actress known for her roles in films such as "The Kissing Booth" series, "The Act," and various other television and movie projects.
-
E.
Katherine Hoult
Katherine Hoult is known as the spouse of Richard Mather.
- 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_69ca82f816bc8190ab321c07d72208c1 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb81874d6c8190bbc0ac832d8a339d |
completed | March 31, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6cdb3b48819091c554539e74812a |
completed | April 2, 2026, 1:19 p.m. |
Created at: March 30, 2026, 6:04 p.m.