Triple
T11433313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buccaneer Archipelago |
E270940
|
entity |
| Predicate | hasHumanImpactLevel |
P92717
|
FINISHED |
| Object | low development pressure |
—
|
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: low development pressure | Statement: [Buccaneer Archipelago, hasHumanImpactLevel, low development pressure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHumanImpactLevel Context triple: [Buccaneer Archipelago, hasHumanImpactLevel, low development pressure]
-
A.
hasImpactScale
Indicates the degree or magnitude of impact that one entity or action has on another, typically expressed along a defined scale.
-
B.
humanImpactLevel
chosen
Indicates the degree or extent to which human activities affect or influence a given entity, system, or environment.
-
C.
hasEnvironmentalImpactType
Indicates that something affects the environment in a specific way categorized by a particular type of impact.
-
D.
hasCanonicalImpactOn
Indicates that one entity exerts a standard, authoritative, or officially recognized influence or effect on another entity.
-
E.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
- 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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d806c485f481909dd3d9b0993f3faf |
completed | April 9, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69d7e71436f88190ac7e45a04ea5c987 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:35 p.m.