Triple
T26449176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oroua River |
E665293
|
entity |
| Predicate | hasLandUseImpact |
P75270
|
FINISHED |
| Object | water quality degradation risk |
—
|
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: water quality degradation risk | Statement: [Oroua River, hasLandUseImpact, water quality degradation risk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandUseImpact Context triple: [Oroua River, hasLandUseImpact, water quality degradation risk]
-
A.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
B.
hasLandUsePressure
chosen
Indicates that an area or entity is subject to demands or stresses from human or other uses of land that may affect its condition or availability.
-
C.
hasConstructionImpact
Indicates that one entity causes or is associated with construction-related effects, changes, or disturbances on another entity or environment.
-
D.
hasEnvironmentalImpactType
Indicates that something affects the environment in a specific way categorized by a particular type of impact.
-
E.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
- 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_69ee883d5040819097dd154643005230 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f71996e1a48190ac59a1d66d7c44e8 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
Created at: April 27, 2026, 12:04 a.m.