Triple
T14680906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Morris Dam |
E344779
|
entity |
| Predicate | floodEventMitigated |
P25048
|
FINISHED |
| Object | 1972 Hurricane Agnes flooding on the Genesee River |
—
|
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: 1972 Hurricane Agnes flooding on the Genesee River | Statement: [Mount Morris Dam, floodEventMitigated, 1972 Hurricane Agnes flooding on the Genesee River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floodEventMitigated Context triple: [Mount Morris Dam, floodEventMitigated, 1972 Hurricane Agnes flooding on the Genesee River]
-
A.
floodEvent
Indicates an occurrence of a flooding event affecting a location, time period, or set of impacted entities.
-
B.
hasFloodProtectionInfrastructure
chosen
Indicates that there exists built or implemented infrastructure designed to protect against or mitigate flooding for the referenced entity.
-
C.
floodConsequence
Indicates the resulting effects, outcomes, or impacts that occur as a consequence of a flood event.
-
D.
floodCause
Indicates that one entity is the cause or source of a flood affecting another entity or area.
-
E.
hasFloodRisk
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb5692284819090f775be8e478522 |
completed | April 14, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69de6579fb7881909becc8f5822b39d4 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.