Triple
T978198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Hanshin earthquake |
E21104
|
entity |
| Predicate | buildingsDamaged |
P1583
|
FINISHED |
| Object | hundreds of thousands |
—
|
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: hundreds of thousands | Statement: [Great Hanshin earthquake, buildingsDamaged, hundreds of thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingsDamaged Context triple: [Great Hanshin earthquake, buildingsDamaged, hundreds of thousands]
-
A.
buildingsDestroyed
chosen
Indicates that one or more buildings have been damaged to the point of destruction as a result of some event or action.
-
B.
areaDestroyed
Indicates that a specified portion or region has been damaged or ruined to the point of destruction.
-
C.
damagedIn
Indicates that an entity has suffered harm, impairment, or destruction as a result of a specified event, process, or condition.
-
D.
damagedBy
Indicates that one entity has caused harm, impairment, or deterioration to another entity.
-
E.
warDamage
Indicates damage that was caused as a direct consequence of war or armed conflict.
- 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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b47861808190be56a7bbd926e658 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a8a3b08190b4538e119b13f7f5 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:40 p.m.