Triple
T7644001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lion King II: Simba’s Pride |
E173075
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Jay Rifkin |
E499055
|
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: Jay Rifkin | Statement: [The Lion King II: Simba’s Pride, musicBy, Jay Rifkin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jay Rifkin Context triple: [The Lion King II: Simba’s Pride, musicBy, Jay Rifkin]
-
A.
Jay Rifkin
chosen
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.
-
B.
Ron Rifkin
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.
-
C.
Alan Rifkin
Alan Rifkin is a writer and essayist known for his reflective, Southern California–centered nonfiction and fiction.
-
D.
Saul M. Rifkin
Saul M. Rifkin is the birth name of American actor Ron Rifkin, known for his work in film, television, and theater.
-
E.
Joel Garreau
Joel Garreau is an American journalist and author best known for popularizing the concept of the "edge city" in urban studies.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faf13858819095262664e1e04eb7 |
completed | March 27, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89acaac6481908ef763647a0ca9b3 |
completed | March 29, 2026, 3:21 a.m. |
Created at: March 27, 2026, 3:58 p.m.