Triple
T10836804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Get Hard |
E255779
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Will Ferrell |
E12114
|
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: Will Ferrell | Statement: [Get Hard, starring, Will Ferrell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Will Ferrell Context triple: [Get Hard, starring, Will Ferrell]
-
A.
Will Ferrell
chosen
Will Ferrell is an American comedian, actor, writer, and producer best known for his work on "Saturday Night Live" and a series of hit comedy films such as "Anchorman" and "Elf."
-
B.
Will Forte
Will Forte is an American actor, comedian, and writer best known for his work on "Saturday Night Live" and for creating and starring in the TV series "The Last Man on Earth."
-
C.
Jon Heder
Jon Heder is an American actor best known for his breakout role in the cult comedy film "Napoleon Dynamite" and subsequent performances in various comedy movies.
-
D.
Owen Wilson
Owen Wilson is an American actor and screenwriter known for his laid-back charm and roles in popular comedies and adventure films such as "Wedding Crashers," "Zoolander," and "Midnight in Paris."
-
E.
Luke Wilson
Luke Wilson is an American actor known for his roles in films such as "The Royal Tenenbaums," "Old School," and "Legally Blonde."
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d746ff70148190b844ab92d796af6c |
completed | April 9, 2026, 6:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e6d27d8c8190b2c8ee9c54cf7fd1 |
completed | April 18, 2026, 8:17 p.m. |
Created at: April 8, 2026, 9:19 p.m.