Triple
T16780885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Cure for Wellness |
E407853
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Mia Goth |
E936002
|
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: Mia Goth | Statement: [A Cure for Wellness, starring, Mia Goth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mia Goth Context triple: [A Cure for Wellness, starring, Mia Goth]
-
A.
Mia Goth
chosen
Mia Goth is an English actress and model known for her roles in arthouse and horror films such as "Nymphomaniac," "Suspiria," and "X."
-
B.
Hannah John-Kamen
Hannah John-Kamen is a British actress known for roles in science fiction and fantasy projects, including her portrayal of Ghost in the Marvel film "Ant-Man and the Wasp."
-
C.
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."
-
D.
Marisa del Toro
Marisa del Toro is one of the children of acclaimed Mexican filmmaker Guillermo del Toro.
-
E.
Clea DuVall
Clea DuVall is an American actress and filmmaker known for her roles in films like "But I'm a Cheerleader," "Girl, Interrupted," and "Argo," as well as for her work in independent cinema and television.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b216726881908ddc9cdc772cd5e4 |
completed | April 18, 2026, 4:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00ab0300e48190ad088cd11098ca34 |
completed | May 10, 2026, 3:57 p.m. |
Created at: April 10, 2026, 5:22 a.m.