Triple
T35498563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katharine |
E1025931
|
entity |
| Predicate | hasCulturalUsageType |
P196229
|
FINISHED |
| Object | personal name |
—
|
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: personal name | Statement: [Katharine, hasCulturalUsageType, personal name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCulturalUsageType Context triple: [Katharine, hasCulturalUsageType, personal name]
-
A.
hasCulturalFeature
Indicates that an entity possesses, includes, or is characterized by a particular cultural element, attribute, or landmark.
-
B.
hasCulturalDimensionWith
Indicates that one entity possesses or is associated with a particular cultural dimension in relation to another entity.
-
C.
hasCulturalScope
Indicates that a relationship or action is limited to, relevant within, or characterized by a particular cultural context or domain.
-
D.
hasCulturalConcept
Indicates that an entity embodies, includes, or is associated with a particular cultural idea, value, practice, or construct.
-
E.
hasCulturalExpression
Indicates that an entity embodies, manifests, or is associated with a particular cultural form, practice, or expression.
- 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_69f76dfc9c60819089c4217d93922615 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fe163a41a0819098403b470e327d29 |
completed | May 8, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fe1358db5c819092570814a37ef5bd |
completed | May 8, 2026, 4:46 p.m. |
| PDg | Predicate description generation | batch_69fe1639613c8190aaf1b4c8e2d861ba |
completed | May 8, 2026, 4:58 p.m. |
Created at: May 3, 2026, 4:04 p.m.