Triple
T1779606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cacapon River |
E39258
|
entity |
| Predicate | waterQuality |
P27141
|
FINISHED |
| Object | generally good |
—
|
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: generally good | Statement: [Cacapon River, waterQuality, generally good]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterQuality Context triple: [Cacapon River, waterQuality, generally good]
-
A.
waterQualityIssues
Indicates that there are problems or concerns with the condition, safety, or suitability of a water source.
-
B.
waterQualityProtection
Indicates efforts, measures, or responsibilities aimed at preserving or improving the cleanliness, safety, and ecological integrity of water resources.
-
C.
waterQualityUse
Indicates the way in which water quality is evaluated, classified, or applied for specific purposes or uses.
-
D.
waterCondition
chosen
Indicates the state or quality of water affecting an entity, such as its cleanliness, safety, or suitability for a particular use.
-
E.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab74dc9d1481908084ef07872a71f8 |
completed | March 7, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69aa61cf3ca881908641fd73ce2f7c9d |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.