Triple
T21011130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All Eyez on Me |
E517548
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
John Raffo
John Raffo is a film editor best known for his work on the biographical drama "All Eyez on Me" about rapper Tupac Shakur.
|
E1462761
|
NE FINISHED |
How this triple was built (4 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: John Raffo | Statement: [All Eyez on Me, editedBy, John Raffo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Raffo Context triple: [All Eyez on Me, editedBy, John Raffo]
-
A.
John Raffo
John Raffo is an American screenwriter best known for writing the biographical martial arts film "Dragon: The Bruce Lee Story."
-
B.
Ray Vitte
Ray Vitte was an American film and television actor active in the 1970s and early 1980s, known for supporting roles in comedies and dramas before his career was cut short by his death in 1983.
-
C.
Roger Ferrer
Roger Ferrer is a French local politician who serves as the mayor of the commune of Estagel in southern France.
-
D.
Lou DeMattei
Lou DeMattei is an American tax attorney best known as the longtime husband of acclaimed novelist Amy Tan.
-
E.
Lou Romano
Lou Romano is an American animator, art director, and voice actor best known for his work with Pixar, including voicing the character Alfredo Linguini in the film "Ratatouille."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: John Raffo Triple: [All Eyez on Me, editedBy, John Raffo]
Generated description
John Raffo is a film editor best known for his work on the biographical drama "All Eyez on Me" about rapper Tupac Shakur.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Raffo Target entity description: John Raffo is a film editor best known for his work on the biographical drama "All Eyez on Me" about rapper Tupac Shakur.
-
A.
John Raffo
John Raffo is an American screenwriter best known for writing the biographical martial arts film "Dragon: The Bruce Lee Story."
-
B.
Ray Vitte
Ray Vitte was an American film and television actor active in the 1970s and early 1980s, known for supporting roles in comedies and dramas before his career was cut short by his death in 1983.
-
C.
Roger Ferrer
Roger Ferrer is a French local politician who serves as the mayor of the commune of Estagel in southern France.
-
D.
Lou DeMattei
Lou DeMattei is an American tax attorney best known as the longtime husband of acclaimed novelist Amy Tan.
-
E.
Lou Romano
Lou Romano is an American animator, art director, and voice actor best known for his work with Pixar, including voicing the character Alfredo Linguini in the film "Ratatouille."
- F. None of above. chosen
Provenance (5 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_69e0b50192308190a284fcc89dd23a49 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc3fdf3c8190abd3db7f5eb503a0 |
completed | April 21, 2026, 4:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a093b60b94081909bea5b8b0cf81447 |
completed | May 17, 2026, 3:52 a.m. |
| NEDg | Description generation | batch_6a093d500adc8190ba08e8a6c1674563 |
completed | May 17, 2026, 4 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a093e445e748190a20721d0718c71bc |
completed | May 17, 2026, 4:04 a.m. |
Created at: April 16, 2026, 1:53 p.m.