Triple
T5353216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gothenburg City Airport |
E102625
|
entity |
| Predicate | languageUsedAtLocation |
P18209
|
FINISHED |
| Object | Swedish |
—
|
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: Swedish | Statement: [Gothenburg City Airport, languageUsedAtLocation, Swedish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedAtLocation Context triple: [Gothenburg City Airport, languageUsedAtLocation, Swedish]
-
A.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
B.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
-
C.
languageUse
chosen
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
D.
majorityLanguageOf
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or entity.
-
E.
languageOfEnvironment
Indicates the language predominantly used or present in a given environment or context.
- 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_69bd43d8f7248190b64c140734b5c9a8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd86149774819084049a8785e3f2e0 |
completed | March 20, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69bd845c6f108190832a8d14b356368a |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:01 p.m.