Triple
T2938683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mauna Kahalawai |
E79330
|
entity |
| Predicate | hasErosionProcess |
P18790
|
FINISHED |
| Object | fluvial erosion |
—
|
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: fluvial erosion | Statement: [Mauna Kahalawai, hasErosionProcess, fluvial erosion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasErosionProcess Context triple: [Mauna Kahalawai, hasErosionProcess, fluvial erosion]
-
A.
hasErosionFeature
Indicates that one entity exhibits or contains a specific erosion-related feature or form resulting from erosional processes.
-
B.
hasWeathering
Indicates that one entity undergoes or exhibits the process of weathering caused by another entity or environmental factors.
-
C.
hasSedimentsThat
Indicates that one entity contains, includes, or is associated with specific sediments described by the related entity.
-
D.
hasSedimentLoad
Indicates that one entity (typically a water body or flow) carries or transports a certain amount or type of sediment associated with another entity.
-
E.
geomorphologicalProcess
chosen
Indicates a relationship where one entity undergoes or is shaped by natural earth-surface processes that modify landforms and terrain structure.
- 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_69ad8b0fbab081908f6a61567c045d8d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad986c1c0c8190a6a9f17082438cfd |
completed | March 8, 2026, 3:40 p.m. |
| PD | Predicate disambiguation | batch_69ad96088fb481909976b436c2b729d9 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:56 p.m.