Triple
T11406400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porky’s Duck Hunt |
E270249
|
entity |
| Predicate | featuresGag |
P58285
|
FINISHED |
| Object | fourth-wall breaking |
—
|
LITERAL 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: fourth-wall breaking | Statement: [Porky’s Duck Hunt, featuresGag, fourth-wall breaking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresGag Context triple: [Porky’s Duck Hunt, featuresGag, fourth-wall breaking]
-
A.
featuresRunningGag
chosen
Indicates that the subject includes or makes use of a recurring joke or humorous motif.
-
B.
featuresIn
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
C.
featuresGroup
Indicates that an entity includes or is associated with a specific group as one of its features or components.
-
D.
featuresSuit
Indicates that one entity includes or presents a particular suit (e.g., clothing, armor, or outfit) as a notable component or attribute.
-
E.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8014c820c81908538ba4a08e13230 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e70ffd708190b62a78ebcbce9f78 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.