Triple
T37758309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Anna River watershed |
E941181
|
entity |
| Predicate | hasImpairmentConcerns |
P192113
|
FINISHED |
| Object | nutrient pollution |
—
|
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: nutrient pollution | Statement: [North Anna River watershed, hasImpairmentConcerns, nutrient pollution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImpairmentConcerns Context triple: [North Anna River watershed, hasImpairmentConcerns, nutrient pollution]
-
A.
hasImpairmentStatus
Indicates that an entity possesses a particular condition of functional limitation, disability, or impairment status.
-
B.
hasImpairmentListing
Indicates that an entity is associated with a specific recognized category or listing of impairments.
-
C.
canImpair
Indicates that one entity has the potential or ability to weaken, damage, or reduce the normal function, quality, or effectiveness of another entity.
-
D.
hasSenseImpairment
Indicates that an entity experiences a reduction or loss in one or more sensory abilities (such as sight, hearing, or touch).
-
E.
hasHealthConcern
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
- F. None of above. chosen
Provenance (4 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_69f76ee1f3a88190834e6c8af99bccc9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69fcf36bb86c8190a0a0ccf47cb56e5c |
completed | May 7, 2026, 8:17 p.m. |
Created at: May 3, 2026, 4:19 p.m.