Information on calling through the API + added details

README.md

@@ -26,7 +26,8 @@ paperswithcode_id: scifi-tv-plots
 ## Table of Contents
 - [Dataset Description](#dataset-description)
   - [Format](#format)
-- [Dataset Structure](#dataset-structure)
+    - [Using the Dataset with Hugging Face](#call-scifi)
+- [Original Dataset Structure](#dataset-structure)
   - [Files in _OriginalStoriesSeparated_ Directory](#original-stories)
 - [Additional Information](#additional-information)
   - [Citation](#citation)
@@ -52,37 +53,59 @@ Total: 2276 stories
 
 Dataset is "eventified" and generalized (see LJ Martin, P Ammanabrolu, X Wang, W Hancock, S Singh, B Harrison, and MO Riedl. Event Representations for Automated Story Generation with Deep Neural Nets, Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018. for details on these processes.) and split into train-test-validation sets—separated by story so that full stories will stay together—for converting events into full sentences.
 
-## Format
+---
+### Format
 | Dataset Split | Number of Stories in Split | Number of Sentences in Split |
 | ------------- |--------------------------- |----------------------------- |
-| Train         | 1738                       | 257,184                      |
+| Train         | 1737                       | 257,108                      |
 | Validation    | 194                        | 32,855                       |
 | Test          | 450                        | 30,938                       |
 
+#### Using the Dataset with Hugging Face
+```
+from datasets import load_dataset
+
+#download and load the data
+dataset = load_dataset('Scifi_TV_Shows') 
+#you can then get the individual splits
+train = dataset['train']
+test = dataset['test']
+validation = dataset['validation']
+```
+Each split has 7 attributes (explained in more detail in the next section):
+```
+>>> print(train)
+
+ Dataset({
+    features: ['story_num', 'story_line', 'event', 'gen_event', 'sent', 'gen_sent', 'entities'],
+    num_rows: 257108
+})
+```
+
 ---
-## Dataset Structure
+## Original Dataset Structure
 * File names: scifi-val.txt, scifi-test.txt, & scifi-train.txt
 * Each sentence of the stories are split into smaller sentences and the events are extracted.
 * Each line of the file contains information about a single sentence, delimited by "|||". Each line contains, in order:
     * The story number
     * The line number (within the story)
-    * 5-tuple events in a list (subject, verb, direct object, modifier noun, preposition)
+    * 5-tuple events in a list (subject, verb, direct object, modifier noun, preposition); e.g., 
     ``
 [[u'Voyager', u'run', 'EmptyParameter', u'deuterium', u'out'], [u'Voyager', u'force', u'go', 'EmptyParameter', 'EmptyParameter'], [u'Voyager', u'go', 'EmptyParameter', u'mode', u'into']]
     ``
-    * generalized 5-tuple events in a list
+    * generalized 5-tuple events in a list; events are generalized using WordNet and VerbNet; e.g., 
     ``
     [['<VESSEL>0', 'function-105.2.1', 'EmptyParameter', "Synset('atom.n.01')", u'out'], ['<VESSEL>0', 'urge-58.1-1', u'escape-51.1-1', 'EmptyParameter', 'EmptyParameter'], ['<VESSEL>0', u'escape-51.1-1', 'EmptyParameter', "Synset('statistic.n.01')", u'into']]
     ``
-    * original sentence
+    * original sentence (These sentences are split to contain fewer events per sentence. For the full original sentence, see the OriginalStoriesSeparated directory.); e.g., 
     ``
     The USS Voyager is running out of deuterium as a fuel and is forced to go into Gray mode.
     ``
-    * generalized sentence
+    * generalized sentence; only nouns are generalized (using WordNet); e.g., 
     ``
     the <VESSEL>0 is running out of Synset('atom.n.01') as a Synset('matter.n.03') and is forced to go into Synset('horse.n.01') Synset('statistic.n.01').
     ``
-    * a dictionary of numbered entities by tag within the entire story (e.g. the second entity in the "&lt;ORGANIZATION>" list in the dictionary would be &lt;ORGANIZATION>1 in the story above&mdash;index starts at 0)
+    * a dictionary of numbered entities by tag within the _entire story_ (e.g. the second entity in the "&lt;ORGANIZATION>" list in the dictionary would be &lt;ORGANIZATION>1 in the story above&mdash;index starts at 0); e.g., 
     ``
     {'<ORGANIZATION>': ['seven of nine', 'silver blood'], '<LOCATION>': ['sickbay', 'astrometrics', 'paris', 'cavern', 'vorik', 'caves'], '<DATE>': ['an hour ago', 'now'], '<MISC>': ['selected works', 'demon class', 'electromagnetic', 'parises', 'mimetic'], '<DURATION>': ['less than a week', 'the past four years', 'thirty seconds', 'an hour', 'two hours'], '<NUMBER>': ['two', 'dozen', '14', '15'], '<ORDINAL>': ['first'], '<PERSON>': ['tom paris', 'harry kim', 'captain kathryn janeway', 'tuvok', 'chakotay', 'jirex', 'neelix', 'the doctor', 'seven', 'ensign kashimuro nozawa', 'green', 'lt jg elanna torres', 'ensign vorik'], '<VESSEL>': ['uss voyager', 'starfleet']}
     ``
@@ -91,6 +114,7 @@ Dataset is "eventified" and generalized (see LJ Martin, P Ammanabrolu, X Wang, W
 * Contains unedited, unparsed original stories scraped from the respective Fandom wikis.
 * Each line is a story with sentences space-separated. After each story, there is a &lt;EOS> tag on a new line.
 * There is one file for each of the 11 domains listed above.
+* These are currently not set up to be called through the Hugging Face API and must be extracted from the zip directly.
 ---
 ## Additional Information
 ### Citation