Triple
T18058921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fridolins visor |
E432113
|
entity |
| Predicate | isOftenReferencedAs |
P83591
|
FINISHED |
| Object | one of Karlfeldt's key works |
—
|
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: one of Karlfeldt's key works | Statement: [Fridolins visor, isOftenReferencedAs, one of Karlfeldt's key works]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenReferencedAs Context triple: [Fridolins visor, isOftenReferencedAs, one of Karlfeldt's key works]
-
A.
oftenCitedAs
Indicates that one entity is frequently referenced or mentioned as an example, source, or authority in relation to another entity.
-
B.
isFrequentlyIncludedIn
Indicates that something is regularly or commonly contained or made part of something else.
-
C.
alsoRefersTo
Indicates that one term, label, or identifier is used as an alternative designation for the same entity or concept as another.
-
D.
oftenRefersTo
chosen
Indicates that one entity is frequently used to mention, denote, or reference another entity in common usage or context.
-
E.
oftenUsedAsNameFor
Indicates that something frequently serves as a name or designation for another entity.
- 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.