Triple
T4150443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Devil All the Time |
E89889
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Haley Bennett |
E151015
|
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: Haley Bennett | Statement: [The Devil All the Time, castMember, Haley Bennett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haley Bennett Context triple: [The Devil All the Time, castMember, Haley Bennett]
-
A.
Haley Bennett
chosen
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."
-
B.
Olivia DeJonge
Olivia DeJonge is an Australian actress known for her role as Priscilla Presley in Baz Luhrmann’s 2022 biographical film "Elvis."
-
C.
Olivia Thirlby
Olivia Thirlby is an American actress known for her roles in films such as "Juno," "Dredd," and various independent and mainstream productions.
-
D.
Juno Temple
Juno Temple is an English actress known for her eclectic film roles and acclaimed performance as Keeley Jones in the television series "Ted Lasso."
-
E.
Dakota Fanning
Dakota Fanning is an American actress who rose to fame as a child star in films like "I Am Sam" and has since built a diverse career in both mainstream and independent cinema.
- 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_69aed95a59a881909b26e70b42c6811a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0274f440819087dd58a9ce45cce5 |
completed | March 9, 2026, 5:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7628a4c81908990727003d8c247 |
completed | March 14, 2026, 7:30 p.m. |
Created at: March 9, 2026, 3:43 p.m.