Triple
T7594225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bering Sea coastal plain |
E179814
|
entity |
| Predicate | processInfluence |
P9
|
FINISHED |
| Object | coastal erosion |
—
|
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: coastal erosion | Statement: [Bering Sea coastal plain, processInfluence, coastal erosion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: processInfluence Context triple: [Bering Sea coastal plain, processInfluence, coastal erosion]
-
A.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
-
B.
influenced
chosen
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
C.
influentialFrom
Indicates that one entity has exerted influence on another, contributing to or shaping the latter’s ideas, behavior, or development.
-
D.
hasSignificantInfluenceIn
Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
-
E.
designInfluenceOn
Indicates that one design, designer, or design-related factor has an effect on shaping, guiding, or altering another design or design outcome.
- 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_69c69f3487ec8190bf7acdf2dd91e6d6 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9bab3a08190a2c36b2c72a1de25 |
completed | March 27, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e2e42c8190afc802c4796c9cc2 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:53 p.m.