Triple
T5571751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Svalbard Airport, Longyear |
E146216
|
entity |
| Predicate | languageUsedForOperations |
P4197
|
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: [Svalbard Airport, Longyear, languageUsedForOperations, Norwegian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedForOperations Context triple: [Svalbard Airport, Longyear, languageUsedForOperations, Norwegian]
-
A.
languageOfOperation
chosen
Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
-
B.
languagesUsed
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
-
C.
languageOfCommand
Indicates that a specified language is the one in which a given command is expressed or issued.
-
D.
tertiaryLanguageOfOperation
Indicates that an entity uses a specified language as its third most prominent or prioritized language of operation.
-
E.
languageOfCode
Indicates that a programming code artifact is written in, or uses, a particular programming language.
- 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020518f348190879ac67dab307134 |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b147cc081909237f3f2967d4cb8 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:37 p.m.