Triple
T2893414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gauley River National Recreation Area |
E63880
|
entity |
| Predicate | whitewaterClassification |
P17791
|
FINISHED |
| Object | Class III |
—
|
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: Class III | Statement: [Gauley River National Recreation Area, whitewaterClassification, Class III]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: whitewaterClassification Context triple: [Gauley River National Recreation Area, whitewaterClassification, Class III]
-
A.
waterwayClass
chosen
Indicates the classification or type of a waterway based on its navigational, functional, or physical characteristics.
-
B.
typeOfWaterfall
Indicates that one entity is a specific kind or category of waterfall in relation to another entity.
-
C.
hasWatercourseType
Indicates the specific kind or category of watercourse (such as river, stream, or canal) associated with an entity.
-
D.
waterwaySystem
Indicates that one entity is part of, or belongs to, a connected network of waterways associated with another entity.
-
E.
riverFeatureType
Indicates the specific kind or category of physical or functional feature associated with a river (e.g., source, mouth, tributary, channel segment).
- 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_69ab4c45822c8190830c5f2bb97bcfd0 |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe062234c81909411e34db7d2683d |
completed | March 7, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_69abdd17bcdc8190aa47274a50ba4ad4 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:07 p.m.