Triple
T30668860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teddy Brewster |
E780737
|
entity |
| Predicate | modeOfDelusion |
P5072
|
FINISHED |
| Object | presidential delusion |
—
|
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: presidential delusion | Statement: [Teddy Brewster, modeOfDelusion, presidential delusion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modeOfDelusion Context triple: [Teddy Brewster, modeOfDelusion, presidential delusion]
-
A.
deceptionMotif
Indicates a relationship where one entity employs or embodies a theme of deceit, trickery, or misleading appearance in relation to another entity or situation.
-
B.
mode
chosen
Indicates the manner, method, or way in which an action, process, or interaction is carried out or occurs.
-
C.
typeOfDeception
Indicates the specific kind or category of deceptive act that one entity employs toward another or in a given context.
-
D.
paradoxType
Indicates the specific kind or category of paradox that characterizes the relationship or situation.
-
E.
correctsAberration
Indicates that one entity counteracts, fixes, or compensates for an error, flaw, or deviation present in 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_69f224a7fc208190a07d6d3879b31640 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68b121eac81909e90416207bc1157 |
completed | May 2, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69f6861170d08190bb98be609d436f84 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:31 p.m.