Triple
T8767556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Fair Maid of Perth |
E208373
|
entity |
| Predicate | hasValentineDayMotif |
P85277
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Fair Maid of Perth, hasValentineDayMotif, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasValentineDayMotif Context triple: [The Fair Maid of Perth, hasValentineDayMotif, true]
-
A.
hasOccasionType
Indicates that an occasion, event, or happening is classified as being of a particular type or category.
-
B.
hasMotiveTheme
Indicates that an action, event, or situation is associated with a central motivating theme or underlying driving idea.
-
C.
hasMottoRibbon
Indicates that an entity features or is associated with a ribbon element specifically used to display a motto.
-
D.
hasDayTheme
Indicates that something is associated with or characterized by a theme specifically intended for daytime use or context.
-
E.
hasFestivalTheme
Indicates that something is associated with, characterized by, or designed around a particular festival-related theme.
- 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_69ca835edb4481909b4aafb616dc5eb7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5eeae70c8190adc2bc2846da0fbf |
completed | March 31, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1884bc8190a46e8308db31f7ab |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cfddef48190aee764ee7b25bae9 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:41 p.m.