Triple
T20728001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yellow Sea Warm Current |
E509488
|
entity |
| Predicate | impactOnHumanActivity |
P43904
|
FINISHED |
| Object | influences regional fisheries productivity |
—
|
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: influences regional fisheries productivity | Statement: [Yellow Sea Warm Current, impactOnHumanActivity, influences regional fisheries productivity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnHumanActivity Context triple: [Yellow Sea Warm Current, impactOnHumanActivity, influences regional fisheries productivity]
-
A.
impactOnHumans
chosen
Indicates a relationship where something produces an effect, influence, or consequence on humans.
-
B.
humanImpact
Indicates the effect or influence that human activities have on another entity, system, or environment.
-
C.
effectOfActivities
Indicates the causal impact that certain activities have on a particular outcome, state, or condition.
-
D.
humanImpactLevel
Indicates the degree or extent to which human activities affect or influence a given entity, system, or environment.
-
E.
socialImpact
Indicates the extent to which an action, entity, or relationship affects society or communities, whether positively or negatively.
- 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_69e0b4c4cc648190b45fda6e2b20af56 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1e9ed708190ad8e371646630fea |
completed | April 21, 2026, 12:16 a.m. |
| PD | Predicate disambiguation | batch_69e5c04b31248190b9b9d91b5cb854e3 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:30 p.m.