Triple
T22128402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Like a Surgeon |
E546847
|
entity |
| Predicate | hasNotableWordplay |
P83584
|
FINISHED |
| Object | puns on medical terminology |
—
|
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: puns on medical terminology | Statement: [Like a Surgeon, hasNotableWordplay, puns on medical terminology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableWordplay Context triple: [Like a Surgeon, hasNotableWordplay, puns on medical terminology]
-
A.
isPlayOnWordsWith
Indicates a relationship where one expression is a pun or wordplay that depends on, echoes, or cleverly twists the wording or meaning of another expression.
-
B.
hasIronicMeaning
Indicates that something conveys a meaning opposite to or incongruent with its literal expression, creating an ironic effect.
-
C.
hasNotableWord
Indicates that an entity is associated with a word or term that is considered notable, distinctive, or significant in some context.
-
D.
taglineWordplay
chosen
Indicates that a tagline employs wordplay, such as puns, double meanings, or playful language, as a key part of its expression.
-
E.
usesDoubleEntendre
Indicates that one entity employs language or expressions with a double meaning, often to convey a hidden or suggestive message alongside a literal one.
- 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_69e11e39bf348190b541bfa16a7b71e0 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12983acfc81908013f66acb31f198 |
completed | April 28, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69e71b384e008190b723c9a0f1089d66 |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:32 p.m.