Triple
T24891298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burrendong Dam |
E623008
|
entity |
| Predicate | hasSignificantDroughtEvent |
P15089
|
FINISHED |
| Object | very low storage during Millennium Drought |
—
|
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: very low storage during Millennium Drought | Statement: [Burrendong Dam, hasSignificantDroughtEvent, very low storage during Millennium Drought]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignificantDroughtEvent Context triple: [Burrendong Dam, hasSignificantDroughtEvent, very low storage during Millennium Drought]
-
A.
droughtDurationYears
Indicates the number of years that a drought condition persists or has persisted.
-
B.
droughtType
Indicates the specific category or classification of a drought affecting an area or system.
-
C.
dateOfMajorDrainageEvent
Indicates the specific date on which a significant drainage-related event (such as major flooding, diversion, or alteration of water flow) occurred.
-
D.
hasDrySeasonCause
Indicates that one factor or condition is the underlying cause of a location or region experiencing a dry season.
-
E.
hasDisaster
chosen
Indicates that an entity experiences, is affected by, or is associated with a disaster event.
- 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_69e2fac597708190a922bf39a49ec70a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f48b9b687881908fd87a2f5fa0b1e7 |
completed | May 1, 2026, 11:16 a.m. |
| PD | Predicate disambiguation | batch_69f48060597c8190a4414e4e4fcb1fec |
completed | May 1, 2026, 10:28 a.m. |
Created at: April 18, 2026, 5:26 a.m.