Triple
T18058920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fridolins visor |
E432113
|
entity |
| Predicate | isOftenStudiedIn |
P46827
|
FINISHED |
| Object | courses on Swedish literature |
—
|
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: courses on Swedish literature | Statement: [Fridolins visor, isOftenStudiedIn, courses on Swedish literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenStudiedIn Context triple: [Fridolins visor, isOftenStudiedIn, courses on Swedish literature]
-
A.
widelyStudiedIn
chosen
Indicates that something has been extensively researched, analyzed, or examined within a particular field, domain, or context.
-
B.
oftenStudiedBetween
Indicates that something is frequently examined, researched, or analyzed in relation to two or more entities.
-
C.
alsoStudied
Indicates that an entity pursued additional studies in another subject, field, or institution besides a primary one.
-
D.
studiedBy
Indicates that a subject (such as a field, topic, or object) is examined, researched, or learned by an agent (such as a person or group).
-
E.
canBeStudiedAs
Indicates that something is suitable or appropriate to be examined, analyzed, or researched as a subject of study.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4c1048c00819097c7dfbf76bb0987 |
completed | April 19, 2026, 11:48 a.m. |
| PD | Predicate disambiguation | batch_69e3f90c652481908133a73106d78919 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:26 a.m.