text stringlengths 1 243 | label int64 0 1 |
|---|---|
complaining
| 0 |
failing to support
| 0 |
desperately needs
| 0 |
many years of decay
| 0 |
no quick fix
| 0 |
is happy
| 0 |
long and painful
| 0 |
nobody is happy
| 0 |
a very complicated process
| 0 |
a decade of dramatic economic decline
| 0 |
suffering from
| 0 |
would surely be higher still
| 0 |
had forbidden
| 0 |
suffering from some intoxication
| 0 |
far from perfect
| 0 |
soured relations between
| 0 |
fell out
| 0 |
mounting rivalry
| 0 |
a hostile nation
| 0 |
have each accused the other
| 0 |
bowed to
| 0 |
totally dependent
| 0 |
lose control
| 0 |
warned
| 0 |
bowed to pressure
| 0 |
to its knees
| 0 |
military adventurism
| 0 |
would boost
| 0 |
threaten
| 0 |
most heavily armed place in the world
| 0 |
dangerous flashpoint
| 0 |
a superficial exercise
| 0 |
accusing
| 0 |
merely speaks
| 0 |
deep divergences
| 0 |
negatively
| 0 |
biased
| 0 |
claims
| 0 |
was biased against
| 0 |
complaints of
| 0 |
suspicions
| 0 |
squeezing
| 0 |
playing with fire
| 0 |
subverts
| 0 |
trying to provoke protests
| 0 |
his mdc lot
| 0 |
will not
| 0 |
most dangerous
| 0 |
shoot the man out of office
| 0 |
that extreme
| 0 |
keen to fight
| 0 |
are agitating
| 0 |
allegedly threatening
| 0 |
will remove you violently
| 0 |
villains
| 0 |
do n't want
| 0 |
challenged
| 0 |
flirting with
| 0 |
at it again
| 0 |
opposed
| 0 |
alleged
| 0 |
wants to speak the language of violence
| 0 |
shoot president mugabe out of office
| 0 |
fears
| 0 |
has refused to bow
| 0 |
parliamentarian
| 0 |
still - tense relationship
| 0 |
our renegade province
| 0 |
unusual
| 0 |
so worried
| 0 |
disapproved
| 0 |
so - called stop - over tactic
| 0 |
will not resort
| 0 |
private diplomacy
| 0 |
protests
| 0 |
opposes
| 0 |
gulf between
| 0 |
do not possess the necessary expertise
| 0 |
is an act of objectionable brutality
| 0 |
just to gain popularity
| 0 |
may feel uneasy
| 0 |
this is a question of
| 0 |
certain excesses
| 0 |
does not function optimally
| 0 |
is colored by leftist ideology
| 0 |
hype
| 0 |
fostering trade anarchy
| 0 |
this is no blind violence but rather targeted violence
| 0 |
there is no alternative to it but conflict , isolation , nationalism , and ultimately war
| 0 |
cold monster
| 0 |
immense gulf between
| 0 |
slow
| 0 |
are needed
| 0 |
the brutality with which this closure was implemented was unheard of
| 0 |
thought
| 0 |
was annoyed
| 0 |
lost the game
| 0 |
but there is little i can do
| 0 |
would totally liberalize
| 0 |
only got worse
| 0 |
End of preview. Expand in Data Studio
Dataset used in the paper:
A thorough benchmark of automatic text classification From traditional approaches to large language models
https://github.com/waashk/atcBench
To guarantee the reproducibility of the obtained results, the dataset and its respective CV train-test partitions is available here.
Each dataset contains the following files:
- data.parquet: pandas DataFrame with texts and associated encoded labels for each document.
- split_<k>.pkl: pandas DataFrame with k-cross validation partition.
- For each fold <k>:
- train_fold_<k>.parquet: pandas DataFrame with texts and associated encoded labels for each document on the training split k (according to split_<k>.pkl)
- train_fold_<k>.parquet: pandas DataFrame with texts and associated encoded labels for each document on the testing split k (according to split_<k>.pkl)
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