Triple
T14536579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | royal palace of Zamunda |
E341057
|
entity |
| Predicate | usedForHumor |
P114828
|
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: [royal palace of Zamunda, usedForHumor, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForHumor Context triple: [royal palace of Zamunda, usedForHumor, yes]
-
A.
usesHumorAsDefense
Indicates that an entity habitually employs humor or joking behavior to cope with, deflect, or protect themselves from emotional discomfort, stress, or vulnerability.
-
B.
hasHumorousTreatmentOf
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
-
C.
humorSetting
Indicates a relationship where one entity specifies or controls the level, style, or presence of humor applied to another entity or context.
-
D.
usedHyperbolically
Indicates that the action or property is being expressed with deliberate exaggeration for emphasis or effect, rather than as a literal statement.
-
E.
parodies
Indicates that one entity imitates another in an exaggerated or humorous way, often to criticize or comment on the original.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb1b9d39881908c7a3a5b17d432af |
completed | April 14, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69de5c546c7081909e27d504ec360c5c |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de610330a48190b558235a14c0dc9f |
completed | April 14, 2026, 3:45 p.m. |
Created at: April 10, 2026, 1:22 a.m.