Triple
T27306101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caroline Island |
E689060
|
entity |
| Predicate | hasLowHumanImpact |
P92717
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Caroline Island, hasLowHumanImpact, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLowHumanImpact Context triple: [Caroline Island, hasLowHumanImpact, true]
-
A.
isLowImpact
Indicates that an action, event, or entity has minimal negative effect or disruption on its surrounding system, environment, or context.
-
B.
humanImpactLevel
chosen
Indicates the degree or extent to which human activities affect or influence a given entity, system, or environment.
-
C.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
D.
landscapeImpact
Indicates how an action, project, or entity alters or affects the visual and physical character of a landscape.
-
E.
hasEnvironmentalImpactType
Indicates that something affects the environment in a specific way categorized by a particular type of impact.
- 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_69ef355b931c8190a63cafaf7bcc008b |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: April 27, 2026, 11:25 a.m.