Triple
T9485112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Fjording |
E228739
|
entity |
| Predicate | languageTheme |
P67042
|
FINISHED |
| Object | Norwegian |
—
|
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: Norwegian | Statement: [The Fjording, languageTheme, Norwegian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageTheme Context triple: [The Fjording, languageTheme, Norwegian]
-
A.
languageOfTheme
Indicates that a particular language is used to express, describe, or label a given theme or subject.
-
B.
styleLanguage
chosen
Indicates a relationship where one entity specifies the language or linguistic style in which another entity is expressed, formatted, or presented.
-
C.
languageName
Indicates the specific name assigned to a language in the relationship.
-
D.
languageFamilyColor
Indicates that a language family is associated with a particular color, typically for visualization or categorization purposes.
-
E.
themeFor
Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
- 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_69ca84730a5081908de282651019bf2f |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd804fb2b4819084c7f5a842dbe5a6 |
completed | April 1, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69cca561e6b0819090aa795f3c3a2083 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:55 p.m.