Triple
T20220637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hustadvika |
E495242
|
entity |
| Predicate | hasMaritimeHazard |
P74048
|
FINISHED |
| Object | rough seas |
—
|
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: rough seas | Statement: [Hustadvika, hasMaritimeHazard, rough seas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaritimeHazard Context triple: [Hustadvika, hasMaritimeHazard, rough seas]
-
A.
maritimeHazard
chosen
Indicates a condition, object, or situation at sea that poses a risk to vessels, navigation, or maritime operations.
-
B.
hasMaritimeFeature
Indicates that one entity possesses, contains, or is characterized by a maritime-related feature such as a sea, coast, harbor, or other oceanic element.
-
C.
hasCoastalRisk
Indicates that an entity is exposed to potential hazards or adverse impacts associated with coastal environments, such as flooding, erosion, or storm surge.
-
D.
hasTsunamiRisk
Indicates that the subject is exposed to or associated with a potential risk of tsunamis.
-
E.
hazardLevelForBoating
Indicates the degree of risk or danger that current conditions pose specifically for boating activities.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66edc88148190b003b72eb4c69da5 |
completed | April 20, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69e55b18609481909ab28bc8750a642f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:39 p.m.