Triple
T23096169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Rwanyakizinga |
E575894
|
entity |
| Predicate | withinEcosystemType |
P102573
|
FINISHED |
| Object | wetland |
—
|
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: wetland | Statement: [Lake Rwanyakizinga, withinEcosystemType, wetland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: withinEcosystemType Context triple: [Lake Rwanyakizinga, withinEcosystemType, wetland]
-
A.
isWithinEcosystem
chosen
Indicates that one entity is located inside, and functionally part of, the ecological system defined by another entity.
-
B.
containsEcosystem
Indicates that one entity encompasses or includes an ecosystem within its boundaries or scope.
-
C.
partOfEcosystem
Indicates that an entity functions as a component within a larger ecological system, contributing to and affected by its interactions and processes.
-
D.
hasNearbyEcosystemType
Indicates that one entity has an ecosystem of a specified type located in its immediate surrounding area.
-
E.
ecosystemIntegrationWith
Indicates how one entity is incorporated into, interacts with, or functions as part of another entity’s broader ecosystem of products, services, or systems.
- 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_69e245c060b48190a9bd61a47a16db17 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18de522e48190a37e6c2fda2de465 |
completed | April 29, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_69ef89e5ce748190b2c3ac3843484127 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 3:57 p.m.