Triple
T2727928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Legend of Good Women |
E60237
|
entity |
| Predicate | settingOfPrologue |
P35676
|
FINISHED |
| Object | dream vision |
—
|
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: dream vision | Statement: [The Legend of Good Women, settingOfPrologue, dream vision]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfPrologue Context triple: [The Legend of Good Women, settingOfPrologue, dream vision]
-
A.
setting
Indicates the place, time, or context in which an event, action, or interaction occurs.
-
B.
includesSpokenPrologue
Indicates that an entity (such as a work or performance) contains a spoken introductory section delivered before the main content begins.
-
C.
hasPrologueSometimes
Indicates that an entity occasionally or in some instances includes a prologue.
-
D.
placeOfSetting
Indicates the location or environment where an event, scene, or situation takes place.
-
E.
storyElement
chosen
Indicates that one entity functions as a narrative component or part within the structure of another entity’s story.
- 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_69ab4b75cd908190b691ef0d1801acda |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdacffa6481909df37335e8fdd595 |
completed | March 7, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69abd82586f88190a98f60d3247fe2d3 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.