Triple
T11327623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julie d’Étanges |
E268261
|
entity |
| Predicate | readerReceptionRole |
P95128
|
FINISHED |
| Object | model of sensibility for 18th-century readers |
—
|
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: model of sensibility for 18th-century readers | Statement: [Julie d’Étanges, readerReceptionRole, model of sensibility for 18th-century readers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readerReceptionRole Context triple: [Julie d’Étanges, readerReceptionRole, model of sensibility for 18th-century readers]
-
A.
readerReception
chosen
Indicates how readers interpret, respond to, or are affected by a particular text or work.
-
B.
audienceRole
Indicates the role or function an entity has as part of an audience in relation to another entity or event.
-
C.
readership
Indicates the relationship in which one party reads, follows, or is the audience for the written or published work of another.
-
D.
roleInReception
Indicates the specific function or capacity an entity serves within the context of a reception event.
-
E.
speakerRole
Indicates the functional role or capacity in which an entity is acting as a speaker within a communicative event.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9e2253881909518cad0f12ef612 |
completed | April 9, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69d787afe5a48190b8af1a3e19529641 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.