Triple
T1840546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caroline Plate |
E41166
|
entity |
| Predicate | hasSeismicity |
P12618
|
FINISHED |
| Object | frequent earthquakes along its boundaries |
—
|
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: frequent earthquakes along its boundaries | Statement: [Caroline Plate, hasSeismicity, frequent earthquakes along its boundaries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeismicity Context triple: [Caroline Plate, hasSeismicity, frequent earthquakes along its boundaries]
-
A.
hasEarthquakes
chosen
Indicates that the specified location or region experiences one or more earthquakes.
-
B.
hasGeologicalActivity
Indicates that an entity exhibits or is associated with ongoing or past geological processes such as volcanism, tectonics, or seismic activity.
-
C.
earthquakeSequence
Indicates a relationship where multiple earthquakes are linked as part of the same temporal or causal sequence of seismic events.
-
D.
hasVolcanicActivity
Indicates that the subject exhibits or is associated with ongoing or past volcanic processes, such as eruptions, lava flows, or related geothermal activity.
-
E.
earthquakeType
Indicates the specific classification or category of an earthquake based on its characteristics or cause.
- 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafdb0d2c8190a67f584e67979fa3 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:33 p.m.