Triple
T7289589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Side to Side |
E163956
|
entity |
| Predicate | usesDoubleEntendre |
P75408
|
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: [Side to Side, usesDoubleEntendre, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDoubleEntendre Context triple: [Side to Side, usesDoubleEntendre, true]
-
A.
hasIronicMeaning
Indicates that something conveys a meaning opposite to or incongruent with its literal expression, creating an ironic effect.
-
B.
usedHyperbolically
Indicates that the action or property is being expressed with deliberate exaggeration for emphasis or effect, rather than as a literal statement.
-
C.
possibleMeaning
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
D.
hasHumorousTreatmentOf
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
-
E.
misinterpretedBy
Indicates that something (such as a statement, action, or signal) is understood incorrectly or in a way not intended by a particular entity.
- 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_69c6886093b88190a254b1ce6db8bae7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb6bde448190b52852c916a8059d |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76c5fbc8190b378830082f11cb0 |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6e82b0f9881909d29c99af1ea0dbf |
completed | March 27, 2026, 8:27 p.m. |
Created at: March 27, 2026, 3 p.m.