Triple
T35695817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Båtsfjord Airport |
E1031435
|
entity |
| Predicate | servesFishingIndustry |
P137299
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Båtsfjord Airport, servesFishingIndustry, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesFishingIndustry Context triple: [Båtsfjord Airport, servesFishingIndustry, true]
-
A.
containsFishery
Indicates that one entity includes, encompasses, or has within its area a fishery or fishing-related operation.
-
B.
supportsFishery
chosen
Indicates that one entity provides resources, conditions, or actions that maintain or enhance the viability of a fishery.
-
C.
fisheryType
Indicates the specific category or kind of fishery associated with an entity, such as its operational or regulatory classification.
-
D.
hasShoreFishing
Indicates that a location or body of water provides opportunities or facilities for fishing from the shore.
-
E.
hasFishingCommunities
Indicates that there exist communities in a given area or entity whose livelihoods or primary activities are based on fishing.
- 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_69f76e0c73ec819080ab60a9e2f5f1f6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a00233e2170819084bee0c8f74cc1a4 |
completed | May 10, 2026, 6:18 a.m. |
| PD | Predicate disambiguation | batch_6a0022943fd08190b73007f080d5971d |
completed | May 10, 2026, 6:15 a.m. |
Created at: May 3, 2026, 4:05 p.m.