Triple
T15050708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Real Capital |
E379352
|
entity |
| Predicate | humorousTone |
P116540
|
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: [The Real Capital, humorousTone, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: humorousTone Context triple: [The Real Capital, humorousTone, true]
-
A.
humorSetting
Indicates a relationship where one entity specifies or controls the level, style, or presence of humor applied to another entity or context.
-
B.
usedForHumor
Indicates that something is employed with the intention of being funny, amusing, or comical.
-
C.
usesHumorAsDefense
Indicates that an entity habitually employs humor or joking behavior to cope with, deflect, or protect themselves from emotional discomfort, stress, or vulnerability.
-
D.
hasHumorousTreatmentOf
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
-
E.
isHumorousCharacter
Indicates that the character is portrayed in a humorous way or primarily serves a comedic role in the context.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69deda8f71988190b4fe7f7de4ccb798 |
completed | April 15, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69de9a69d7848190b2b4662dd30f20e9 |
completed | April 14, 2026, 7:50 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 3:01 a.m.