Triple
T17977524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In Time |
E449514
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Alex Pettyfer |
—
|
NE NERFINISHED |
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: Alex Pettyfer | Statement: [In Time, starring, Alex Pettyfer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alex Pettyfer Context triple: [In Time, starring, Alex Pettyfer]
-
A.
Alex Pettyfer
chosen
Alex Pettyfer is an English actor and model known for roles in films such as "Stormbreaker," "I Am Number Four," and "Magic Mike."
-
B.
Alan Ritchson
Alan Ritchson is an American actor, model, and filmmaker best known for roles in projects like "Reacher," "Blue Mountain State," and the "Teenage Mutant Ninja Turtles" films.
-
C.
Ethan Embry
Ethan Embry is an American actor known for his roles in 1990s films such as "Empire Records," "Can't Hardly Wait," and various television series.
-
D.
Doug Hutchison
Doug Hutchison is an American character actor best known for his roles in films like "The Green Mile" and TV series such as "The X-Files" and "Lost."
-
E.
Nicholas Woodeson
Nicholas Woodeson is a British character actor known for his work in film, television, and theatre, including roles in productions such as "Skyfall," "Rome," and "The Death of Stalin."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b200e9108190bcdde5ba7938ba94 |
completed | April 19, 2026, 10:44 a.m. |
Created at: April 10, 2026, 10:22 a.m.