Triple
T34702781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naked Gun 33⅓: The Final Insult – film score |
E1000418
|
entity |
| Predicate | mainCharacterDepicted |
P118235
|
FINISHED |
| Object | Frank Drebin |
—
|
NE NERFINISHED |
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: Frank Drebin | Statement: [Naked Gun 33⅓: The Final Insult – film score, mainCharacterDepicted, Frank Drebin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterDepicted Context triple: [Naked Gun 33⅓: The Final Insult – film score, mainCharacterDepicted, Frank Drebin]
-
A.
depictsCharacterType
Indicates that one entity visually represents or portrays a character of a specified type or role.
-
B.
depictedSubject
Indicates that one entity visually represents or portrays another entity as its subject in an image or depiction.
-
C.
portraysMainCharacter
chosen
Indicates that one entity depicts or represents another entity as the primary or central character in a work or narrative.
-
D.
literaryCharacterDepicted
Indicates that a literary character is visually or textually represented in a work such as an image, illustration, or other medium.
-
E.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
- F. None of above.
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_69f76dab937881909c86f1b9ad50445f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fd2a215d6c8190a1a428ccaee603f1 |
completed | May 8, 2026, 12:11 a.m. |
| PD | Predicate disambiguation | batch_69fd28ef19688190bb8370f2812a43e7 |
completed | May 8, 2026, 12:06 a.m. |
Created at: May 3, 2026, 3:59 p.m.