Update README.md

README.md

@@ -87,12 +87,14 @@ published at ACL 2020.
 
 
 
+
 ### Supported Tasks and Leaderboards
 - **Tasks:** Relation Classification
 - **Leaderboards:** [https://paperswithcode.com/sota/relation-extraction-on-tacred](https://paperswithcode.com/sota/relation-extraction-on-tacred)
 
 ### Languages
-The language in the dataset is English.
+The languages in the dataset are Arabic, German, English, Spanish, Finnish, French, Hindi, Hungarian, Japanese, Polish, Russian, Turkish, and Chinese.
+All languages except English are machine-translated using either Deepl's or Google's translation APIs.
 ## Dataset Structure
 ### Data Instances
 - **Size of downloaded dataset files:** 62.3 MB
@@ -117,7 +119,7 @@ An example of 'train' looks as follows:
 The data fields are the same among all splits.
 
 - `id`: the instance id of this sentence
-- `tokens`: the list of tokens of this sentence, obtained with the StanfordNLP toolkit.
+- `token`: the list of tokens of this sentence, obtained with the StanfordNLP toolkit.
 - `relation`: the relation label of this instance.
 - `subj_start`: the 0-based index of the start token of the relation subject mention.
 - `subj_end`: the 0-based index of the end token of the relation subject mention, exclusive.
@@ -126,10 +128,27 @@ The data fields are the same among all splits.
 - `obj_end`: the 0-based index of the end token of the relation object mention, exclusive.
 - `obj_type`: the NER type of the object mention, among 23 fine-grained types used in the [Stanford NER system](https://stanfordnlp.github.io/CoreNLP/ner.html).
 ### Data Splits
-To miminize dataset bias, TACRED is stratified across years in which the TAC KBP challenge was run:
-|           | Train  |  Dev  | Test |
+To miminize dataset bias, TACRED is stratified across years in which the TAC KBP challenge was run.
+Languages statistics for the splits differ because not all instances could be translated with the
+subject and object entity markup still intact, these were discarded.
+
+|    Language (Translation Engine - D = Deepl, G = Google)       | Train  |  Dev  | Test |
 | -----     | ------ | ----- | ---- |
-| TACRED     | 68,124 (TAC KBP 2009-2012) | 22,631 (TAC KBP 2013) | 15,509 (TAC KBP 2014) |
+| English (en)    | 68,124 (TAC KBP 2009-2012) | 22,631 (TAC KBP 2013) | 15,509 (TAC KBP 2014) |
+| en (-)   |  68,124 |  22,631 |  15,509 |
+| ar (G)   |  67,736 |  22,502 |  15,425 |
+| de (D)   |  67,205 |  22,343 |  15,282 |
+| es (D)   |  65,247 |  21,697 |  14,908 |
+| fi (D)   |  66,751 |  22,268 |  15,083 |
+| fr (D)   |  66,856 |  22,248 |  15,237 |
+| hi (G)   |  67,751 |  22,511 |  15,440 |
+| hu (G)   |  67,766 |  22,519 |  15,436 |
+| ja (D)   |  61,571 |  20,290 |  13,701 |
+| pl (G)   |  68,124 |  22,631 |  15,509 |
+| ru (D)   |  66,413 |  21,998 |  14,995 |
+| tr (G)   |  67,652 |  22,510 |  15,429 |
+| zh (D)   |  65,211 |  21,490 |  14,694 |
+
 ## Dataset Creation
 ### Curation Rationale
 [More Information Needed]