Triple
T25727369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sagami Trough |
E645145
|
entity |
| Predicate | lastMajorEarthquake |
P55087
|
FINISHED |
| Object | 1923 Great Kanto earthquake |
—
|
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: 1923 Great Kanto earthquake | Statement: [Sagami Trough, lastMajorEarthquake, 1923 Great Kanto earthquake]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lastMajorEarthquake Context triple: [Sagami Trough, lastMajorEarthquake, 1923 Great Kanto earthquake]
-
A.
lastMajorEarthquakeName
chosen
Indicates the name of the most recent major earthquake associated with a given entity (such as a location or region).
-
B.
lastMajorEarthquakeYear
Indicates the calendar year in which the most recent major earthquake affecting the referenced entity occurred.
-
C.
lastKnownGreatEarthquakeGenerated
Indicates that the referenced event is the most recent known great earthquake that produced or generated the associated effect or data.
-
D.
largestEarthquakeDate
Indicates the date on which the largest earthquake in a given context occurred.
-
E.
deadliestEarthquakeUntil
Indicates that one earthquake was the most lethal (had caused the highest number of deaths) of all earthquakes up to a specified point in time.
- 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_69e77e85254081908d79ee4e8715f283 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fcb8c1908190968e113a3f6f0929 |
completed | May 2, 2026, 1:31 p.m. |
| PD | Predicate disambiguation | batch_69f480824a1c81908a8a492eedbc2596 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 11:06 p.m.