Triple
T31494788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sumas Prairie |
E803504
|
entity |
| Predicate | impactOf2021Floods |
P124172
|
FINISHED |
| Object | widespread agricultural damage |
—
|
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: widespread agricultural damage | Statement: [Sumas Prairie, impactOf2021Floods, widespread agricultural damage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOf2021Floods Context triple: [Sumas Prairie, impactOf2021Floods, widespread agricultural damage]
-
A.
floodConsequence
Indicates the resulting effects, outcomes, or impacts that occur as a consequence of a flood event.
-
B.
impactOfDisasters
chosen
Indicates the effects or consequences that disasters have on entities, conditions, or outcomes.
-
C.
notableFloodEvents
Indicates that there are significant or historically important flood occurrences associated with the given entity.
-
D.
yearOfMajorFlooding
Indicates the specific year in which a major flooding event occurred for the associated entity.
-
E.
floodEvent
Indicates an occurrence of a flooding event affecting a location, time period, or set of impacted entities.
- 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_69f348ca04508190ba9379b5329dfd75 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
Created at: April 30, 2026, 9:40 p.m.