Triple
T3646885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nankai Trough |
E77321
|
entity |
| Predicate | earthquakeRecurrenceInterval |
P28046
|
FINISHED |
| Object | approximately 100–200 years |
—
|
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: approximately 100–200 years | Statement: [Nankai Trough, earthquakeRecurrenceInterval, approximately 100–200 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earthquakeRecurrenceInterval Context triple: [Nankai Trough, earthquakeRecurrenceInterval, approximately 100–200 years]
-
A.
earthquakeSequence
Indicates a relationship where multiple earthquakes are linked as part of the same temporal or causal sequence of seismic events.
-
B.
earthquakeMagnitude
Indicates the measured strength or intensity of an earthquake, typically expressed on a standardized magnitude scale.
-
C.
recurrenceIntervalEstimate
chosen
Indicates an estimated length of time between successive occurrences of the same event or condition.
-
D.
earthquakeHazardLevel
Indicates the assessed degree of risk or potential impact from earthquakes associated with a given location or entity.
-
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_69ad85de1b988190a45f8dbfebc806fc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3895198819090a17a8894e91d00 |
completed | March 8, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69adb8445b2c8190ab07f6ad4e010d0e |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:24 p.m.