Triple
T37956892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohandas B.A.L.L.B. |
E946890
|
entity |
| Predicate | hasSatiricalTakeOn |
P161912
|
FINISHED |
| Object | legal system |
—
|
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: legal system | Statement: [Mohandas B.A.L.L.B., hasSatiricalTakeOn, legal system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSatiricalTakeOn Context triple: [Mohandas B.A.L.L.B., hasSatiricalTakeOn, legal system]
-
A.
hasSatiricalTone
Indicates that something expresses its content in a mocking, ironic, or humorous way to criticize or ridicule its subject.
-
B.
hasNotableSatire
Indicates that one entity is recognized for containing or exemplifying a significant satirical treatment of the other entity.
-
C.
satirizedBy
chosen
Indicates that the subject is the target or object of satire created or performed by the specified entity.
-
D.
hasHumorousTreatmentOf
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
-
E.
usedForHumor
Indicates that something is employed with the intention of being funny, amusing, or comical.
- 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_69f76ef64cf08190ad3e1114b62aac67 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: May 3, 2026, 4:20 p.m.