Triple
T25965377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Hervey, 2nd Baron Hervey |
E645650
|
entity |
| Predicate | satiricalTargetOf |
P113884
|
FINISHED |
| Object | Alexander Pope |
—
|
NE NERFINISHED |
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: Alexander Pope | Statement: [John Hervey, 2nd Baron Hervey, satiricalTargetOf, Alexander Pope]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: satiricalTargetOf Context triple: [John Hervey, 2nd Baron Hervey, satiricalTargetOf, Alexander Pope]
-
A.
hasSatiricalTone
Indicates that something expresses its content in a mocking, ironic, or humorous way to criticize or ridicule its subject.
-
B.
politicalIdeologyParodies
Indicates a relationship where one entity creates or embodies a parody that humorously imitates, critiques, or exaggerates another entity’s political ideology.
-
C.
roleInSatire
chosen
Indicates that an entity serves as a character, target, or contributing element within a satirical work or satirical context.
-
D.
notablePrankTarget
Indicates that the subject is a well-known or frequent target of pranks carried out by the object.
-
E.
hasHumorousTreatmentOf
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
- 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_69e77e85efc08190997da7fcf98bd300 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f604c9e74c819090333e44f00abd17 |
completed | May 2, 2026, 2:06 p.m. |
| PD | Predicate disambiguation | batch_69f4a10480748190a2e67bd399fc435d |
completed | May 1, 2026, 12:48 p.m. |
Created at: April 22, 2026, 8:48 a.m.