Triple
T12949120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2005 Kashmir earthquake |
E309842
|
entity |
| Predicate | schoolsDestroyed |
P1583
|
FINISHED |
| Object | 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: thousands | Statement: [2005 Kashmir earthquake, schoolsDestroyed, thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: schoolsDestroyed Context triple: [2005 Kashmir earthquake, schoolsDestroyed, 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.
worksDestroyedBy
Indicates that certain works have been ruined, demolished, or rendered unusable as a result of the actions or effects of a specified agent or cause.
-
D.
sufferedDestructionIn
Indicates that an entity experienced damage, ruin, or devastation during or as part of a specified event or period.
-
E.
demolishedOrDestroyed
Indicates that one entity has caused another entity to be torn down, ruined, or rendered unusable, typically through deliberate demolition or destructive force.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:43 p.m.