Triple
T12753020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taos Plateau volcanic field |
E304781
|
entity |
| Predicate | geologicHazardLevel |
P106714
|
FINISHED |
| Object | low in historic time |
—
|
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: low in historic time | Statement: [Taos Plateau volcanic field, geologicHazardLevel, low in historic time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geologicHazardLevel Context triple: [Taos Plateau volcanic field, geologicHazardLevel, low in historic time]
-
A.
earthquakeHazardLevel
Indicates the assessed degree of risk or potential impact from earthquakes associated with a given location or entity.
-
B.
geologicalHazardZoneFor
Indicates a relationship where a specified area or zone is identified as being at risk from a particular geological hazard (such as earthquakes, landslides, or volcanic activity).
-
C.
riskToEarth
Indicates that something poses a potential threat, danger, or harmful impact to Earth.
-
D.
hasNaturalHazardRisk
Indicates that an entity is exposed or subject to potential damage or impact from one or more natural hazards (e.g., earthquakes, floods, storms).
-
E.
frequentNaturalHazard
Indicates that a location or area regularly experiences natural hazards such as floods, earthquakes, storms, or similar events with notable frequency.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96406e97c8190b79081039847115c |
completed | April 10, 2026, 8:56 p.m. |
| PDg | Predicate description generation | batch_69d96d87078c819083ea724238992204 |
completed | April 10, 2026, 9:37 p.m. |
Created at: April 9, 2026, 5:27 p.m.