Triple
T32445342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saharan Air Layer |
E829127
|
entity |
| Predicate | affectsHealth |
P19730
|
FINISHED |
| Object | respiratory irritation |
—
|
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: respiratory irritation | Statement: [Saharan Air Layer, affectsHealth, respiratory irritation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectsHealth Context triple: [Saharan Air Layer, affectsHealth, respiratory irritation]
-
A.
healthEffect
chosen
Indicates the impact or consequence that one entity has on the health or well-being of another.
-
B.
affectsPhenomenon
Indicates that one phenomenon produces an influence or change on another phenomenon.
-
C.
alsoAffects
Indicates that an action, condition, or change impacting one entity additionally impacts another entity as well.
-
D.
effectOnHealthCare
Indicates the impact or influence that something has on the quality, accessibility, cost, or delivery of health care services.
-
E.
healthTheme
Indicates that the subject is associated with, focuses on, or is characterized by a particular health-related topic or theme.
- 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_69f3491d2e5c819092b1c9535beff8ec |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: May 1, 2026, 12:56 a.m.