Triple
T37234238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kitri (Don Quixote) |
E923524
|
entity |
| Predicate | nationalStyleAssociation |
P59353
|
FINISHED |
| Object | Spanish style |
—
|
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: Spanish style | Statement: [Kitri (Don Quixote), nationalStyleAssociation, Spanish style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalStyleAssociation Context triple: [Kitri (Don Quixote), nationalStyleAssociation, Spanish style]
-
A.
nationalStyle
Indicates that something is characterized by or associated with the distinctive style of a particular nation.
-
B.
heritageStyle
Indicates that one entity is characterized by, designed in, or associated with a particular heritage or traditional style defined by the other entity.
-
C.
architecturalStyle
Indicates the architectural design tradition, movement, or style that characterizes the form and appearance of a structure or built work.
-
D.
interiorStyle
Indicates that one entity has a particular interior design style or aesthetic characterized by the other entity.
-
E.
originCountryStyle
chosen
Indicates that something is characterized by or created in the style or manner typical of a particular country of origin.
- 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_69f76ea9fee88190a589f661d95a7189 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe12a899d4819080d48423f32eace9 |
completed | May 8, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69fe0d7f6aa08190a1d2dfc025d4e0dc |
completed | May 8, 2026, 4:21 p.m. |
Created at: May 3, 2026, 4:15 p.m.