Triple
T33754674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noresund |
E864942
|
entity |
| Predicate | hasNearbyWaterRecreation |
P155301
|
FINISHED |
| Object | boating on Krøderen |
—
|
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: boating on Krøderen | Statement: [Noresund, hasNearbyWaterRecreation, boating on Krøderen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyWaterRecreation Context triple: [Noresund, hasNearbyWaterRecreation, boating on Krøderen]
-
A.
hasRecreationalActivityNearby
chosen
Indicates that a location has one or more recreational activities or facilities available in its nearby surroundings.
-
B.
hasRecreationalUseNearby
Indicates that there is at least one location or facility for recreational activities situated close to the referenced entity.
-
C.
hasNearbyWater
Indicates that one entity is located close to a body of water associated with or relevant to another entity.
-
D.
hasNearbyWatersUsedBy
Indicates that a body of water located near an entity is utilized or accessed by another specified entity.
-
E.
hasCoastalRecreation
Indicates that an entity provides, supports, or is associated with recreational activities occurring along a coast or shoreline.
- 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_69f3498c35f881909df279ae4270f831 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff8aff48988190a48a440de8238ef9 |
completed | May 9, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69ff8a780404819082f48ceb21e7fe11 |
completed | May 9, 2026, 7:26 p.m. |
Created at: May 1, 2026, 1:45 a.m.