Triple
T24891299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burrendong Dam |
E623008
|
entity |
| Predicate | hasSignificantFloodEvent |
P39409
|
FINISHED |
| Object | major inflows during 2010–2011 floods |
—
|
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: major inflows during 2010–2011 floods | Statement: [Burrendong Dam, hasSignificantFloodEvent, major inflows during 2010–2011 floods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignificantFloodEvent Context triple: [Burrendong Dam, hasSignificantFloodEvent, major inflows during 2010–2011 floods]
-
A.
notableFloodEvents
chosen
Indicates that there are significant or historically important flood occurrences associated with the given entity.
-
B.
floodEvent
Indicates an occurrence of a flooding event affecting a location, time period, or set of impacted entities.
-
C.
yearOfMajorFlooding
Indicates the specific year in which a major flooding event occurred for the associated entity.
-
D.
hasFloodRisk
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
-
E.
hasFloodHistory
Indicates that the subject has experienced one or more flood events in the past.
- 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_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
Created at: April 18, 2026, 5:26 a.m.