Triple
T21708228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Obelix |
E535825
|
entity |
| Predicate | reasonForRunningGag |
P145034
|
FINISHED |
| Object | already permanently super-strong |
—
|
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: already permanently super-strong | Statement: [Obelix, reasonForRunningGag, already permanently super-strong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForRunningGag Context triple: [Obelix, reasonForRunningGag, already permanently super-strong]
-
A.
notableGag
Indicates that something features a particularly memorable or significant joke, comedic moment, or running gag.
-
B.
humorSetting
Indicates a relationship where one entity specifies or controls the level, style, or presence of humor applied to another entity or context.
-
C.
featuresMotherInLawGags
Indicates a relationship where content includes or focuses on jokes, pranks, or humorous situations involving a mother-in-law.
-
D.
usedForHumor
Indicates that something is employed with the intention of being funny, amusing, or comical.
-
E.
reasonForCurse
Indicates the cause, justification, or triggering event that led to a curse being placed on someone or something.
- 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_69e0c46b44c0819088ab883ebd44e0e8 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb5314a288190b4b8347cca15aaa8 |
completed | April 27, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69e6969113cc8190ab69855ef5667e4b |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69b4aa2b48190830107391e81571a |
completed | April 20, 2026, 9:31 p.m. |
Created at: April 16, 2026, 6:46 p.m.