Triple
T30176136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duckman |
E767062
|
entity |
| Predicate | containsAdultHumor |
P14479
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Duckman, containsAdultHumor, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsAdultHumor Context triple: [Duckman, containsAdultHumor, true]
-
A.
containsAdultContent
Indicates that the referenced item includes material intended for adults, such as explicit sexual, violent, or otherwise age-restricted content.
-
B.
hasComedyElements
Indicates that something contains humorous or comedic aspects as part of its overall content or style.
-
C.
hasHumorFunction
Indicates that something serves a humorous role or purpose, such as eliciting amusement, laughter, or comedic effect.
-
D.
hasHumorType
chosen
Indicates that an entity possesses or is characterized by a particular style, category, or type of humor.
-
E.
hasAdultRank
Indicates that an entity holds a status or position classified as an adult-level rank within a given system or hierarchy.
- 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_69f2247ba20c81909d34f2bfed706e1e |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fedec693b08190b0f8bfdb921e0766 |
completed | May 9, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69fede16c1d48190a20d8a9c5722c307 |
completed | May 9, 2026, 7:11 a.m. |
Created at: April 29, 2026, 7:25 p.m.