Triple
T3402906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Sudeikis |
E71697
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jason Sudeikis |
E71697
|
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: Jason Sudeikis | Statement: [Jason Sudeikis, name, Jason Sudeikis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jason Sudeikis Context triple: [Jason Sudeikis, name, Jason Sudeikis]
-
A.
Jason Sudeikis
chosen
Jason Sudeikis is an American actor, comedian, writer, and producer best known for his work on "Saturday Night Live" and for creating and starring in the acclaimed series "Ted Lasso."
-
B.
Joel McHale
Joel McHale is an American actor, comedian, and television host best known for leading the satirical series "The Soup" and starring on the sitcom "Community."
-
C.
Bill Hader
Bill Hader is an American actor, comedian, writer, and director best known for his work on Saturday Night Live and for creating and starring in the dark comedy series Barry.
-
D.
B. J. Novak
B. J. Novak is an American actor, writer, comedian, and director best known for his work on the U.S. version of "The Office."
-
E.
Rob Riggle
Rob Riggle is an American actor, comedian, and former Marine officer known for his energetic, often over-the-top roles in film and television comedies.
- 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_69ad85aac4808190a092c9cc8911f584 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb8e78ec8819089417666dc29f412 |
completed | March 8, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34bd4d02881909c365e054148ae8c |
completed | March 12, 2026, 11:27 p.m. |
Created at: March 8, 2026, 3:14 p.m.