Triple
T21716462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casita |
E536042
|
entity |
| Predicate | disasterCauseDetail |
P145070
|
FINISHED |
| Object | intense rainfall from Hurricane Mitch saturating volcanic slopes |
—
|
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: intense rainfall from Hurricane Mitch saturating volcanic slopes | Statement: [Casita, disasterCauseDetail, intense rainfall from Hurricane Mitch saturating volcanic slopes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disasterCauseDetail Context triple: [Casita, disasterCauseDetail, intense rainfall from Hurricane Mitch saturating volcanic slopes]
-
A.
causeOfDisaster
Indicates that the subject is responsible for bringing about or triggering the specified disaster.
-
B.
notableDisasterType
Indicates the specific kind or category of disaster for which something (such as a place, event, or entity) is notable or best known.
-
C.
disasterLocation
Indicates the place where a disaster occurs or has its primary impact.
-
D.
disasterDepicted
Indicates that one entity visually represents or portrays a disaster involving or affecting another entity.
-
E.
disasterName
Indicates the specific name or title assigned to a particular disaster event.
- F. None of above. chosen
Provenance (4 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_69e0c46c6dd88190a595375fa6ebd701 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efd96ab4c88190b76f4a6b7c855039 |
completed | April 27, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69e6969725bc81908e7ad19619ba2688 |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69b4aa2b48190830107391e81571a |
completed | April 20, 2026, 9:31 p.m. |
Created at: April 16, 2026, 6:47 p.m.