Triple
T10788039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Paris Wife |
E254497
|
entity |
| Predicate | literaryMovementDepicted |
P56599
|
FINISHED |
| Object | modernism |
—
|
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: modernism | Statement: [The Paris Wife, literaryMovementDepicted, modernism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryMovementDepicted Context triple: [The Paris Wife, literaryMovementDepicted, modernism]
-
A.
literaryMovement
Indicates the artistic or intellectual movement in literature with which a work, author, or text is associated or to which it belongs.
-
B.
literaryPeriodOfWork
chosen
Indicates the literary period or movement to which a particular work belongs.
-
C.
literarySubject
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
D.
literaryThemeInvolvement
Indicates the involvement or presence of a particular literary theme within a work, passage, or character arc.
-
E.
literaryTradition
Indicates a relationship where a work, practice, or expression belongs to, arises from, or participates in a particular established body of literary customs, styles, or conventions.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732d65fcc8190ab5573a861409c56 |
completed | April 9, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69d6f316940c819092a96c429629fdef |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.