Triple
T1121468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Burley Griffin |
E24619
|
entity |
| Predicate | waterQualityIssues |
P25191
|
FINISHED |
| Object | blue-green algae blooms |
—
|
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: blue-green algae blooms | Statement: [Lake Burley Griffin, waterQualityIssues, blue-green algae blooms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterQualityIssues Context triple: [Lake Burley Griffin, waterQualityIssues, blue-green algae blooms]
-
A.
waterQualityUse
Indicates the way in which water quality is evaluated, classified, or applied for specific purposes or uses.
-
B.
hasWaterQualityHistory
Indicates that an entity is associated with a record or series of records describing changes or measurements of its water quality over time.
-
C.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
-
D.
waterSource
Indicates that one entity serves as the source or provider of water for another entity.
-
E.
waterInfrastructure
Indicates the existence, development, or management of systems and facilities that supply, store, treat, or distribute water between entities.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4749ac8190b0fbddac2e9b2586 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bc47fce48190825d3a877251f789 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:43 p.m.