Triple
T18117851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Sinabung |
E433654
|
entity |
| Predicate | causedEvacuationsOf |
P23041
|
FINISHED |
| Object | tens of thousands of people |
—
|
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: tens of thousands of people | Statement: [Mount Sinabung, causedEvacuationsOf, tens of thousands of people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causedEvacuationsOf Context triple: [Mount Sinabung, causedEvacuationsOf, tens of thousands of people]
-
A.
numberOfEvacuated
Indicates the total count of individuals who have been evacuated from a location or situation.
-
B.
evacuatedBy
Indicates that an entity is removed or cleared from a place or situation through the action or assistance of another agent or process.
-
C.
evacuatedDuring
Indicates that one entity was removed or relocated from a place or situation during the time period or event represented by the other entity.
-
D.
notableEvacuation
chosen
Indicates a significant, widely recognized instance of people being moved or fleeing from a place for safety, typically due to danger or emergency conditions.
-
E.
numberOfEvacuatedSettlements
Indicates the total count of settlements that have been evacuated.
- 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd737708190863fba97cdc20d88 |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:28 a.m.