Update README.md

README.md

@@ -36,15 +36,8 @@ For each ORG-PROD combination, the dataset contains an instance, labeled with ei
 
 ### Direct Use
 
-The dataset can be used for binary relation extraction.
+The dataset can be used for binary relation classification.
 
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
 
 ## Dataset Structure
 
@@ -52,9 +45,24 @@ The dataset can be used for binary relation extraction.
 used to create the splits, relationships between data points, etc. -->
 The original dataset was annotated at the document level. We used a random 80/10/10 split to create train, dev and test sets. The documents in each split
 were then converted to sentence-level JSONL files. The test set documents contained a larger number of ORG and PROD annotations than the dev split, which resulted
-in a larger test split in the JSONL version.
+in a larger test split in the JSONL version. Sentence splitting and tokenization were performed with Spacy 3.2.0, using the `en_core_web_sm' model. The JSON field
+structure follows the structure used in the TACRED dataset and includes fields for 'grammar' and 'type', which are somewhat redundant in our case.
+of the JSON follows
+
+Each instance of the dataset contains the following fields:
+- id: the instance id of this sentence, a string feature
+- tokens: the list of tokens of this sentence, a list feature
+- label: the relation label, either "CompanyProvidesProduct" or "no_relation"
+- entities: the token-based start and end offsets of the head (ORG) and tail (PROD) entities, a list feature
+- grammar: a fixed ["SUBJ", "OBJ"] list, since we do not include inverted relations
+- type: a fixed ["ORGANIZATION", "PRODUCT"] list, denoting the entity types of the head and tail entities
+
+## Data Splits
+
+| Train | Validation | Test |
+|-------|------------|------|
+| 2437  |    330     |  510 |
 
-[More Information Needed]
 
 ## Dataset Creation
 
@@ -122,7 +130,7 @@ Users should be made aware of the risks, biases and limitations of the dataset.
 <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
 
 **BibTeX:**
-
+```
 @InProceedings{SCHÖN18.88,
   author = {Saskia Schön and Veselina Mironova and Aleksandra Gabryszak and Leonhard Hennig},
   title = "{A Corpus Study and Annotation Schema for Named Entity Recognition and Relation Extraction of Business Products}",
@@ -135,6 +143,13 @@ Users should be made aware of the risks, biases and limitations of the dataset.
   isbn = {979-10-95546-00-9},
   language = {english}
   }
+```
 
 **APA:**
+```
 Schön, S., Mironova, V., Gabryszak, A., & Hennig, L. (2018). A Corpus Study and Annotation Schema for Named Entity Recognition and Relation Extraction of Business Products. ArXiv, abs/2004.03287.
+```
+
+### Contributions
+
+Thanks to [@leonhardhennig](https://github.com/leonhardhennig) for adding this dataset.