Triple
T17668374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krokstadelva |
E440446
|
entity |
| Predicate | hasNearbyIndustrialSites |
P20649
|
FINISHED |
| Object | along Drammenselva river |
—
|
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: along Drammenselva river | Statement: [Krokstadelva, hasNearbyIndustrialSites, along Drammenselva river]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyIndustrialSites Context triple: [Krokstadelva, hasNearbyIndustrialSites, along Drammenselva river]
-
A.
hasIndustrialSiteIn
Indicates that an entity possesses, operates, or is responsible for an industrial facility located within a specified place or area.
-
B.
hasNearbyIndustry
chosen
Indicates that an entity is located close to one or more industrial facilities or activities.
-
C.
hasIndustrialPlant
Indicates that an entity possesses, operates, or is associated with an industrial plant facility.
-
D.
connectsToIndustrialArea
Indicates that one entity has a direct link, route, or access connection to an industrial area.
-
E.
adjacentToIndustrialArea
Indicates that one entity is located directly next to or bordering an industrial area.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f6723d081908eaa57eef6d70bd0 |
completed | April 19, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69e3cde007d8819090dd92eea9f022cc |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 9:58 a.m.