Triple
T14670758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Ritter |
E344505
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jason Ritter |
E344505
|
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 Ritter | Statement: [Jason Ritter, name, Jason Ritter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jason Ritter Context triple: [Jason Ritter, name, Jason Ritter]
-
A.
Jason Ritter
chosen
Jason Ritter is an American actor known for his work in film and television, including roles in series like "Parenthood" and "Joan of Arcadia."
-
B.
Seth Gabel
Seth Gabel is an American actor known for his roles in television series such as "Fringe," "Salem," and "Nip/Tuck."
-
C.
Gene Draper
Gene Draper is the infant son of Don and Betty Draper on the television series "Mad Men," named after Betty's late father.
-
D.
Sean Garrett
Sean Garrett is an American songwriter and record producer known for crafting numerous chart-topping R&B and hip-hop hits for major artists in the 2000s and 2010s.
-
E.
Eric Bauza
Eric Bauza is a Canadian voice actor and comedian best known for portraying iconic animated characters in modern Looney Tunes productions.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb54ef2908190b189ced65eec434a |
completed | April 14, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e7772508190bee1eb310aa40372 |
completed | May 9, 2026, 12:23 a.m. |
Created at: April 10, 2026, 1:27 a.m.