Triple
T34289714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lauren Wando |
E879849
|
entity |
| Predicate | associatedWithDisasterType |
P205390
|
FINISHED |
| Object | volcanic disaster |
—
|
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: volcanic disaster | Statement: [Lauren Wando, associatedWithDisasterType, volcanic disaster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithDisasterType Context triple: [Lauren Wando, associatedWithDisasterType, volcanic disaster]
-
A.
typeOfDisaster
Indicates that one entity is classified as a specific kind or category of disaster in relation to another entity.
-
B.
supportsDisasterType
Indicates that one entity is capable of handling, responding to, or being applicable to a specified type of disaster.
-
C.
disasterDepicted
Indicates that one entity visually represents or portrays a disaster involving or affecting another entity.
-
D.
notableDisasterType
Indicates the specific kind or category of disaster for which something (such as a place, event, or entity) is notable or best known.
-
E.
hasDisaster
Indicates that an entity experiences, is affected by, or is associated with a 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_69f349b6df1c81908e5e5b6c2ab6409b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:57 a.m.