Triple
T27451541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Páez River |
E692454
|
entity |
| Predicate | naturalDisasterEvent |
P155803
|
FINISHED |
| Object | 1994 Páez River disaster |
—
|
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: 1994 Páez River disaster | Statement: [Páez River, naturalDisasterEvent, 1994 Páez River disaster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: naturalDisasterEvent Context triple: [Páez River, naturalDisasterEvent, 1994 Páez River disaster]
-
A.
notableDisasterType
Indicates the specific kind or category of disaster for which something (such as a place, event, or entity) is notable or best known.
-
B.
typeOfDisaster
chosen
Indicates that one entity is classified as a specific kind or category of disaster in relation to another entity.
-
C.
disasterName
Indicates the specific name or title assigned to a particular disaster event.
-
D.
frequentNaturalHazard
Indicates that a location or area regularly experiences natural hazards such as floods, earthquakes, storms, or similar events with notable frequency.
-
E.
disasterOrWeatherTheme
Indicates that something is associated with, characterized by, or thematically focused on disasters or weather-related events.
- 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_69ef5206c9248190b5975c2a7f9d229c |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f643ed0b7481908cf25f3afec0a61d |
completed | May 2, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f641dc8ff48190ab575d855616580c |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 12:47 p.m.