Triple
T5985287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanto Daishinsai |
E133210
|
entity |
| Predicate | seismicIntensity |
P34010
|
FINISHED |
| Object | very strong to extreme in Tokyo |
—
|
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: very strong to extreme in Tokyo | Statement: [Kanto Daishinsai, seismicIntensity, very strong to extreme in Tokyo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seismicIntensity Context triple: [Kanto Daishinsai, seismicIntensity, very strong to extreme in Tokyo]
-
A.
earthquakeMagnitude
Indicates the measured strength or intensity of an earthquake, typically expressed on a standardized magnitude scale.
-
B.
earthquakeHazardLevel
chosen
Indicates the assessed degree of risk or potential impact from earthquakes associated with a given location or entity.
-
C.
seismicSignificance
Indicates the degree to which something is relevant, influential, or important in the context of seismic activity or earthquake-related phenomena.
-
D.
earthquakeType
Indicates the specific classification or category of an earthquake based on its characteristics or cause.
-
E.
notableEarthquake
Indicates that an earthquake event is significant or noteworthy due to its magnitude, impact, or historical importance.
- 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04a6dcaf08190bac27c7042e65e07 |
completed | March 22, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69c049de98648190962b14fd341c93da |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:04 p.m.