Triple
T36893976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jobu |
E911836
|
entity |
| Predicate | typeOfFictionalElement |
P81118
|
FINISHED |
| Object | running gag |
—
|
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: running gag | Statement: [Jobu, typeOfFictionalElement, running gag]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfFictionalElement Context triple: [Jobu, typeOfFictionalElement, running gag]
-
A.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
B.
bodyTypeInFiction
Indicates how a particular body type is portrayed, characterized, or represented within fictional works.
-
C.
hasFictionalGenreCharacteristic
Indicates that something possesses a specific characteristic or attribute related to a fictional genre.
-
D.
fictionalEntityType
chosen
Indicates that the subject is classified as a particular type or category of fictional entity within a narrative or imaginary context.
-
E.
typeOfCharacter
Indicates that one entity is a specific kind or category of character in relation to another entity.
- 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_69f76e841b54819097e7fa768bbc70b2 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a0332a08b48819094aaed6e04a36886 |
completed | May 12, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_6a0331998a688190b5d919697d4231ac |
completed | May 12, 2026, 1:56 p.m. |
Created at: May 3, 2026, 4:13 p.m.