Triple
T32402484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1985 eruption of Nevado del Ruiz |
E827988
|
entity |
| Predicate | deadliestImpactLocation |
P117952
|
FINISHED |
| Object | Armero |
—
|
NE NERFINISHED |
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: Armero | Statement: [1985 eruption of Nevado del Ruiz, deadliestImpactLocation, Armero]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deadliestImpactLocation Context triple: [1985 eruption of Nevado del Ruiz, deadliestImpactLocation, Armero]
-
A.
disasterLocation
Indicates the place where a disaster occurs or has its primary impact.
-
B.
fatalitiesLocation
chosen
Indicates the place where deaths or fatal incidents occurred.
-
C.
deadliestShockEpicenter
Indicates that the subject is the epicenter location of the deadliest shock (earthquake event) within a given context or dataset.
-
D.
sectorMostAffected
Indicates that a particular sector is the one experiencing the greatest impact or disruption relative to others in a given context.
-
E.
deadliestFor
Indicates that one entity causes the greatest number of deaths or is most lethal specifically with respect to another entity or group.
- 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_69f34919342c8190a4c3bf35a90d4e58 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c21bb0d081909644ca365aacfdfa |
completed | May 3, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 12:53 a.m.