Triple
T24325992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Letter from an Unknown Woman |
E613100
|
entity |
| Predicate | hasLetterAsPlotDevice |
P23847
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Letter from an Unknown Woman, hasLetterAsPlotDevice, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLetterAsPlotDevice Context triple: [Letter from an Unknown Woman, hasLetterAsPlotDevice, yes]
-
A.
centralPlotDevice
Indicates that one entity functions as the main narrative mechanism or element around which the plot of the other entity is structured.
-
B.
hasEnigmaticCharacter
Indicates that something possesses a mysterious, puzzling, or difficult-to-interpret quality or nature.
-
C.
hasNarrativeDevice
chosen
Indicates that one entity employs, contains, or is characterized by a particular narrative device used in storytelling or discourse.
-
D.
hasPoliticalPlot
Indicates that the subject work contains a storyline or narrative element centered on politics, political events, or political power struggles.
-
E.
hasLetter
Indicates that one entity contains, includes, or is associated with a specific letter or character.
- 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_69e2d7db6d5c819091194918157a7c1f |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f292edb6f481909f0a6a7592fd7d6a |
completed | April 29, 2026, 11:23 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:54 a.m.