Update README.md

README.md

@@ -22,7 +22,7 @@ task_categories:
 task_ids:
 - multi-class-classification
 ---
-# Dataset Card for "tacred"
+# Dataset Card for "TACRED"
 ## Table of Contents
 - [Table of Contents](#table-of-contents)
 - [Dataset Description](#dataset-description)
@@ -59,6 +59,8 @@ The TAC Relation Extraction Dataset (TACRED) is a large-scale relation extractio
 and org:members) or are labeled as no_relation if no defined relation is held. These examples are created by combining available human annotations from the TAC
 KBP challenges and crowdsourcing. Please see [Stanford's EMNLP paper](https://nlp.stanford.edu/pubs/zhang2017tacred.pdf), or their [EMNLP slides](https://nlp.stanford.edu/projects/tacred/files/position-emnlp2017.pdf) for full details.
 
+To use the dataset reader, you need to obtain the data from the Linguistic Data Consortium: https://catalog.ldc.upenn.edu/LDC2018T24.
+
 Note: 
 - There is currently a [label-corrected version](https://github.com/DFKI-NLP/tacrev) of the TACRED dataset, which you should consider using instead of
 the original version released in 2017. For more details on this new version, see the [TACRED Revisited paper](https://aclanthology.org/2020.acl-main.142/)
@@ -181,7 +183,7 @@ For the revised version (`"revisited"`), please also cite:
  month = jul,
  year = "2020",
  address = "Online",
- publisher = "Association for Computational Linguistics",
+ publisher = "Association for Computational Linguistics",https://catalog.ldc.upenn.edu/LDC2018T24
  url = "https://www.aclweb.org/anthology/2020.acl-main.142",
  doi = "10.18653/v1/2020.acl-main.142",
  pages = "1558--1569",