Triple
T33439352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1993 Midwest floods |
E856316
|
entity |
| Predicate | leveeFailures |
P18126
|
FINISHED |
| Object | hundreds of levee breaches |
—
|
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: hundreds of levee breaches | Statement: [1993 Midwest floods, leveeFailures, hundreds of levee breaches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leveeFailures Context triple: [1993 Midwest floods, leveeFailures, hundreds of levee breaches]
-
A.
dikeBreaches
chosen
Indicates that a dike fails or ruptures, allowing water to break through its barrier.
-
B.
notableFloodEvents
Indicates that there are significant or historically important flood occurrences associated with the given entity.
-
C.
floodCause
Indicates that one entity is the cause or source of a flood affecting another entity or area.
-
D.
floodEvent
Indicates an occurrence of a flooding event affecting a location, time period, or set of impacted entities.
-
E.
floodRecord
Indicates that an entity serves as a documented record or report of a flood event affecting another entity or area.
- 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_69f34971b75881908be360bb041f003c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e4887e888190ad28da9a74581291 |
completed | May 3, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69f6e3da41948190a4cfe866ce184f73 |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:37 a.m.