Triple
T21767349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Affected Ladies |
E537327
|
entity |
| Predicate | characterTypeSatirized |
P113884
|
FINISHED |
| Object | précieuses |
—
|
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: précieuses | Statement: [The Affected Ladies, characterTypeSatirized, précieuses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterTypeSatirized Context triple: [The Affected Ladies, characterTypeSatirized, précieuses]
-
A.
roleInSatire
chosen
Indicates that an entity serves as a character, target, or contributing element within a satirical work or satirical context.
-
B.
semiAutobiographicalCharacter
Indicates that a character is based partly on the real-life experiences, personality, or identity of its creator or author, but is not a fully direct self-portrayal.
-
C.
isHumorousCharacter
Indicates that the character is portrayed in a humorous way or primarily serves a comedic role in the context.
-
D.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
E.
cultCharacter
Indicates that one entity is a character who is venerated, worshipped, or centrally revered within the cult associated with the other 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_69e0c46f5d1c8190bf830409e98464e5 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f031ab57808190b9af6d8f0ead1051 |
completed | April 28, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69e6be6299988190a34c98fa76d94700 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:51 p.m.