Triple
T24377782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 Central Italy earthquakes |
E614524
|
entity |
| Predicate | deadliestShockEpicenter |
P155975
|
FINISHED |
| Object | near Accumoli, Lazio |
—
|
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: near Accumoli, Lazio | Statement: [2016 Central Italy earthquakes, deadliestShockEpicenter, near Accumoli, Lazio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deadliestShockEpicenter Context triple: [2016 Central Italy earthquakes, deadliestShockEpicenter, near Accumoli, Lazio]
-
A.
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.
-
B.
epicenter
Indicates the central point or focal location from which an event, influence, or effect originates or is most intensely experienced.
-
C.
earthquakeCasualties
Indicates that an earthquake event resulted in a specified number or set of casualties (deaths and/or injuries).
-
D.
deadliestIn
Indicates that something has the highest lethality or causes the most deaths within a specified context, group, or location.
-
E.
strongestShakingArea
Indicates the area that experiences the most intense level of shaking relative to surrounding regions.
- 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_69e2d7e362e481909e32fe4ef8269d4f |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293d96e7c8190b2f33a8fd12c32c6 |
completed | April 29, 2026, 11:27 p.m. |
| PD | Predicate disambiguation | batch_69f287bb1b2c81909c2e7fcc392ad143 |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:02 a.m.