Triple
T3432822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macintyre River basin |
E72377
|
entity |
| Predicate | hasAquaticEcosystem |
P48221
|
FINISHED |
| Object | inland riverine wetlands |
—
|
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: inland riverine wetlands | Statement: [Macintyre River basin, hasAquaticEcosystem, inland riverine wetlands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAquaticEcosystem Context triple: [Macintyre River basin, hasAquaticEcosystem, inland riverine wetlands]
-
A.
hasMarineEcosystem
Indicates that an entity possesses, contains, or is associated with a marine ecosystem as part of its characteristics or environment.
-
B.
hasMarineEcoregion
Indicates that an entity is associated with, or located within, a specific marine ecoregion.
-
C.
hasHydrosphere
Indicates that an entity possesses or is characterized by a surrounding layer or system of water, such as oceans, seas, lakes, or other bodies of liquid water.
-
D.
receivesFreshwaterFrom
Indicates that one entity is supplied with or obtains freshwater from another entity as its source.
-
E.
isFreshwaterBody
Indicates that the referenced body of water consists primarily of non-saline (fresh) water rather than saltwater.
- F. None of above. chosen
Provenance (4 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_69ad85ae14308190bcbc25cfa0246c0b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9c077d48190bee40795cab3e422 |
completed | March 8, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69adae00ad588190bef24373b58a2e1a |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaed74ecc8190b74dc70ab59a3e1c |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:15 p.m.