Triple
T9473718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Goodman |
E228456
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Jason Danieley |
E707892
|
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 Danieley | Statement: [Dan Goodman, portrayedBy, Jason Danieley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jason Danieley Context triple: [Dan Goodman, portrayedBy, Jason Danieley]
-
A.
Jason Danieley
chosen
Jason Danieley is an American musical theatre actor and singer known for his acclaimed performances on Broadway and in concert.
-
B.
Justin Hartley
Justin Hartley is an American actor best known for his television roles in series such as "This Is Us," "Smallville," and "The Young and the Restless."
-
C.
Dustin Milligan
Dustin Milligan is a Canadian actor best known for his roles in the TV series 90210 and the comedy Schitt's Creek.
-
D.
Scott Oake
Scott Oake is a Canadian sportscaster best known for his long-running work as a rinkside reporter and host on national hockey broadcasts.
-
E.
Dylan Walsh
Dylan Walsh is an American actor best known for his role as Dr. Sean McNamara on the television series "Nip/Tuck."
- 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_69ca847162c48190b079076c9595513c |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ff23aec8190b5341eb9bd816a43 |
completed | April 1, 2026, 8:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d25743261881909b207405d5eaa4cd |
completed | April 5, 2026, 12:36 p.m. |
Created at: March 30, 2026, 7:54 p.m.