Triple
T26898581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dippy Dawg |
E677959
|
entity |
| Predicate | hasCharacteristicLaugh |
P174341
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Dippy Dawg, hasCharacteristicLaugh, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharacteristicLaugh Context triple: [Dippy Dawg, hasCharacteristicLaugh, yes]
-
A.
hasLaughTrack
Indicates that a piece of media includes an added or artificial laughter audio track accompanying its content.
-
B.
hasHumorFunction
Indicates that something serves a humorous role or purpose, such as eliciting amusement, laughter, or comedic effect.
-
C.
isHumorousCharacter
Indicates that the character is portrayed in a humorous way or primarily serves a comedic role in the context.
-
D.
hasHumanCharacteristic
Indicates that an entity possesses a trait, quality, or behavior typically associated with humans.
-
E.
hasHumorType
Indicates that an entity possesses or is characterized by a particular style, category, or type of humor.
- F. None of above. chosen
Provenance (4 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f6c20f209081909fb9ac8f95069f04 |
completed | May 3, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
| PDg | Predicate description generation | batch_69f6c125695c81909704c67bef4ce5b2 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 27, 2026, 5:49 a.m.