Triple
T7259207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ron Rifkin |
E159603
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ron Rifkin |
E159603
|
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: Ron Rifkin | Statement: [Ron Rifkin, name, Ron Rifkin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ron Rifkin Context triple: [Ron Rifkin, name, Ron Rifkin]
-
A.
Ron Rifkin
chosen
Ron Rifkin is an American actor known for his character roles in film, television, and theater, including prominent parts in series like "Alias" and numerous stage productions.
-
B.
Jay Rifkin
Jay Rifkin is an American music producer and entrepreneur best known for his collaborations with Hans Zimmer and his work on Disney projects such as The Lion King.
-
C.
Ben Karlin
Ben Karlin is an American television writer and producer best known for his work on The Daily Show and The Colbert Report.
-
D.
Fred Raskin
Fred Raskin is an American film editor best known for his work on several Quentin Tarantino films, including "Django Unchained," "The Hateful Eight," and "Once Upon a Time in Hollywood."
-
E.
Todd Lieberman
Todd Lieberman is an American film producer known for his work on acclaimed movies such as "The Fighter" and other major Hollywood 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_69c68838f9948190875fd60b2351230c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eac340a0819084015a5fbf7a5539 |
completed | March 27, 2026, 8:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7d3b99af08190a28d77e7363edf45 |
completed | March 28, 2026, 1:12 p.m. |
Created at: March 27, 2026, 2:57 p.m.