Triple
T19499180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1953 Ionian earthquake |
E487854
|
entity |
| Predicate | buildingsDamagedOrDestroyedPercentage |
P136151
|
FINISHED |
| Object | about 90% of buildings on Kefalonia and Zakynthos |
—
|
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: about 90% of buildings on Kefalonia and Zakynthos | Statement: [1953 Ionian earthquake, buildingsDamagedOrDestroyedPercentage, about 90% of buildings on Kefalonia and Zakynthos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingsDamagedOrDestroyedPercentage Context triple: [1953 Ionian earthquake, buildingsDamagedOrDestroyedPercentage, about 90% of buildings on Kefalonia and Zakynthos]
-
A.
buildingsDestroyed
Indicates that one or more buildings have been damaged to the point of destruction as a result of some event or action.
-
B.
numberOfDistrictsHeavilyDamaged
Indicates the count of districts that have sustained severe or heavy damage in a given context or event.
-
C.
numberOfBusinessesDestroyed
Indicates the quantity of businesses that have been destroyed in a given event or context.
-
D.
areaDestroyed
Indicates that a specified portion or region has been damaged or ruined to the point of destruction.
-
E.
sufferedDestructionIn
Indicates that an entity experienced damage, ruin, or devastation during or as part of a specified event or period.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6349462108190bb763b4e03bf000d |
completed | April 20, 2026, 2:13 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004d3a708190a1c13c8f644f3926 |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:40 p.m.