Triple
T10124594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Born on the Fourth of July |
E226178
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Jerry Levine |
E596765
|
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: Jerry Levine | Statement: [Born on the Fourth of July, castMember, Jerry Levine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jerry Levine Context triple: [Born on the Fourth of July, castMember, Jerry Levine]
-
A.
Jerry Levine
chosen
Jerry Levine is an American actor and director best known for his roles in 1980s films and television, including a prominent part in the movie Teen Wolf.
-
B.
Dan Levine
Dan Levine is a film producer best known for his work on the acclaimed science-fiction drama "Arrival."
-
C.
Peter Guber
Peter Guber is an American film producer, entrepreneur, and sports team owner known for his leadership roles with major franchises like the Los Angeles Dodgers and Golden State Warriors.
-
D.
Eugene Applebaum
Eugene Applebaum was a prominent Detroit businessman and philanthropist known for founding the Arbor Drugs pharmacy chain and supporting higher education and healthcare initiatives.
-
E.
Jeffrey Silver
Jeffrey Silver is a film producer known for his work on major Hollywood movies, including the science fiction action film "Terminator Salvation."
- 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_69ca843057b48190a86730167f5d6b98 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cdd2ebe4548190a484c145639d92f0 |
completed | April 2, 2026, 2:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cc5cb62081908f4725de14916c11 |
completed | April 5, 2026, 8:55 p.m. |
Created at: March 30, 2026, 9:05 p.m.