Triple
T48151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holland, Michigan |
E945
|
entity |
| Predicate | hasCulturalFeature |
P3114
|
FINISHED |
| Object | Dutch-themed shops and attractions |
—
|
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: Dutch-themed shops and attractions | Statement: [Holland, Michigan, hasCulturalFeature, Dutch-themed shops and attractions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCulturalFeature Context triple: [Holland, Michigan, hasCulturalFeature, Dutch-themed shops and attractions]
-
A.
hasCulturalSignificance
Indicates that something holds notable meaning, value, or importance within a particular culture or cultural context.
-
B.
hasCulturalSignificanceFor
Indicates that something holds particular cultural meaning, value, or importance for a specified group or community.
-
C.
hasAssociatedCulture
Indicates that an entity is related to, influenced by, or characterized by a particular culture.
-
D.
hasCulturalImpact
Indicates that one entity has influenced, shaped, or significantly affected the culture, values, practices, or artistic expressions of another.
-
E.
hasHeritage
Indicates that an entity possesses or is associated with a particular cultural, ethnic, or ancestral background.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24c1a5c14819088748317a3f262c8 |
completed | Feb. 28, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69a24abe7cb481908d969e54032f6c75 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24c198e74819088a211001d0b54d4 |
completed | Feb. 28, 2026, 1:59 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.