Triple
T12976873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drag Me to Hell |
E321546
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Justin Long |
E513584
|
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: Justin Long | Statement: [Drag Me to Hell, starring, Justin Long]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Justin Long Context triple: [Drag Me to Hell, starring, Justin Long]
-
A.
Justin Long
chosen
Justin Long is an American actor known for his comedic and romantic comedy roles in films like "Dodgeball," "Accepted," and the "I'm a Mac" Apple commercials.
-
B.
Steve Kinnaman
Steve Kinnaman is the father of Swedish-American actor Joel Kinnaman.
-
C.
Josh Lucas
Josh Lucas is an American actor known for his roles in films such as "Sweet Home Alabama," "A Beautiful Mind," and "Glory Road," as well as numerous television appearances.
-
D.
Josh Stewart
Josh Stewart is an American actor known for his roles in films like "The Collector" series and "The Dark Knight Rises" as well as television shows such as "Criminal Minds."
-
E.
Justin Bamber
Justin Bamber is a relatively obscure individual whose primary current notability appears to stem from being listed as a bearer of the surname Bamber.
- 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e48c0208190bb7ec80780480b37 |
completed | April 10, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eacea664819096940ba4d409d264 |
completed | May 3, 2026, 6:27 a.m. |
Created at: April 9, 2026, 8:38 p.m.