Triple
T1247901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taliban |
E26807
|
entity |
| Predicate | yearOfDestructionOfBamiyanBuddhas |
P11807
|
FINISHED |
| Object | 2001 |
—
|
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: 2001 | Statement: [Taliban, yearOfDestructionOfBamiyanBuddhas, 2001]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfDestructionOfBamiyanBuddhas Context triple: [Taliban, yearOfDestructionOfBamiyanBuddhas, 2001]
-
A.
lastMajorTempleClosed
Indicates the time or event at which the final significant temple associated with an entity was permanently closed.
-
B.
yearOfDisappearance
Indicates the specific year in which an entity disappeared or ceased to be present.
-
C.
hasCauseOfDestruction
Indicates that one entity is the cause or agent responsible for the destruction or damage of another entity.
-
D.
destructionYear
chosen
Indicates the year in which an entity was destroyed or ceased to exist due to destructive events or actions.
-
E.
buildingsDestroyed
Indicates that one or more buildings have been damaged to the point of destruction as a result of some event or action.
- 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_69a49487a9c48190ba9b05348fd1b53f |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf827e088190a16d845cea14f2c9 |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6b075881908e867c25b5080e25 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.