Triple
T4948064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Decameron |
E111098
|
entity |
| Predicate | hasDayTheme |
P60111
|
FINISHED |
| Object | stories of fortune |
—
|
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: stories of fortune | Statement: [The Decameron, hasDayTheme, stories of fortune]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDayTheme Context triple: [The Decameron, hasDayTheme, stories of fortune]
-
A.
hasDays
Indicates that an entity is associated with, spans, or occurs on specific days.
-
B.
hasSeasonTheme
Indicates that something is associated with or characterized by a particular seasonal theme.
-
C.
hasPersonalThemes
Indicates that something (such as a work, message, or expression) involves themes that are personal, intimate, or directly related to an individual’s own experiences or inner life.
-
D.
hasThemedLand
Indicates that one entity (typically a larger venue or park) includes or is composed of a specific themed land or area as part of its layout or structure.
-
E.
observesDay
Indicates that an entity recognizes, commemorates, or practices a particular day (such as a holiday, event, or observance) according to some calendar or tradition.
- F. None of above. chosen
Provenance (4 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd716520f08190862249efb2058fd4 |
completed | March 20, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3aa1388190b3e0c8ee1ba1e4fa |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd6fa2d2088190ae444d3d0e47d5d2 |
completed | March 20, 2026, 4:02 p.m. |
Created at: March 20, 2026, 1:31 p.m.