Update README.md

README.md

@@ -120,7 +120,7 @@ The data fields are the same among all splits.
 
 
 - `id`: the instance id of this sentence, a `string` feature.
-- `token`: the list of tokens of this sentence, obtained with the StanfordNLP toolkit, a `list` of `string` features.
+- `token`: the list of tokens of this sentence, a `list` of `string` features.
 - `relation`: the relation label of this instance, a `string` classification label.
 - `subj_start`: the 0-based index of the start token of the relation subject mention, an `ìnt` feature.
 - `subj_end`: the 0-based index of the end token of the relation subject mention, exclusive, an `ìnt` feature.
@@ -164,6 +164,8 @@ See the Stanford paper and the Tacred Revisited paper, plus their appendices.
 To ensure that models trained on TACRED are not biased towards predicting false positives on real-world text,
 all sampled sentences where no relation was found between the mention pairs were fully annotated to be negative examples. As a result, 79.5% of the examples
 are labeled as no_relation.
+
+Tokenization of the English data was done with Stanford CoreNLP by the authors of the original dataset. The translated versions were tokenized with language-specific Spacy models (Spacy 3.1) or Trankit when there was no Spacy model for a given language (Hungarian, Turkish, Arabic, Hindi).
 #### Who are the annotators?
 [More Information Needed]
 ### Personal and Sensitive Information