Triple
T10836812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Get Hard |
E255779
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Michael L. Sale |
E891644
|
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: Michael L. Sale | Statement: [Get Hard, editedBy, Michael L. Sale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael L. Sale Context triple: [Get Hard, editedBy, Michael L. Sale]
-
A.
Michael L. Sale
Michael L. Sale is a film editor known for his work on major Hollywood comedies, including the hit movie "Bridesmaids."
-
B.
Michael L. Sale
chosen
Michael L. Sale is an editor known for his work on the publication "Central Intelligence."
-
C.
Michael J. Weithorn
Michael J. Weithorn is an American television writer and producer best known for creating and working on several sitcoms, including "Ned and Stacey" and "The King of Queens."
-
D.
Michael W. Burns
Michael W. Burns is an actor known for his role in the Western television miniseries "Broken Trail."
-
E.
Eric A. Sears
Eric A. Sears is a film editor known for his work on the 2015 horror-comedy movie "Krampus."
- 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_69e23b7578688190975c087d28808be5 |
completed | April 17, 2026, 1:53 p.m. |
Created at: April 8, 2026, 9:19 p.m.