--Standord Natural Language Inference [^ 1]
| Text | Judgments | Hypothesis |
|---|---|---|
| A man inspects the uniform of a figure in some East Asian country. | contradiction | The man is sleeping |
| An older and younger man smiling. | neutral | Two men are smiling and laughing at the cats playing on the floor. |
| A black race car starts up in front of a crowd of people. | contradiction | A man is driving down a lonely road. |
| A soccer game with multiple males playing. | entailment | Some men are playing a sport. |
| A smiling costumed woman is holding an umbrella. | neutral | A happy woman in a fairy costume holds an umbrella. |
Anzahl der Daten: insgesamt 570.000
Training: 550.000
Validierung: 10.000
Test: 10.000
Es gibt auch Syntaxanalysedaten im folgenden Format.
{
"annotator_labels": ["neutral"],
"captionID": "3416050480.jpg#4",
"gold_label": "neutral",
"pairID": "3416050480.jpg#4r1n",
"sentence1": "A person on a horse jumps over a broken down airplane.",
"sentence1_binary_parse": "( ( ( A person ) ( on ( a horse ) ) ) ( ( jumps ( over ( a ( broken ( down airplane ) ) ) ) ) . ) )",
"sentence1_parse": "(ROOT (S (NP (NP (DT A) (NN person)) (PP (IN on) (NP (DT a) (NN horse)))) (VP (VBZ jumps) (PP (IN over) (NP (DT a) (JJ broken) (JJ down) (NN airplane)))) (. .)))",
"sentence2": "A person is training his horse for a competition.",
"sentence2_binary_parse": "( ( A person ) ( ( is ( ( training ( his horse ) ) ( for ( a competition ) ) ) ) . ) )",
"sentence2_parse": "(ROOT (S (NP (DT A) (NN person)) (VP (VBZ is) (VP (VBG training) (NP (PRP$ his) (NN horse)) (PP (IN for) (NP (DT a) (NN competition))))) (. .)))"
}
Sie können es von The Stanford Natural Language Inference (SNLI) Corpus herunterladen.
wget https://nlp.stanford.edu/projects/snli/snli_1.0.zip
unzip snli_1.0.zip
Die Daten werden im json-Format (.jsonl) und im tsv-Format (.txt) gespeichert.
import pandas as pd
df = pd.read_csv("snli_1.0/snli_1.0_train.txt", sep="\t")
References
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