Update README.md

README.md

@@ -40,20 +40,75 @@ factions that we compiled.
 For more information see: [ArXiv](http://arxiv.org/abs/1111.11111)
 
 
+
+## Usage
+
+#### Option 1: HuggingFace
+  For the [All Features Sentences](#all_features_sentences) subset:
+  ```python
+  from datasets import load_dataset
+  knesset_corpus = load_dataset("HaifaCLGroup/knessetCorpus", name="all_features_sentences")
+  
+  ```
+  For the [Non-Morphological Features Sentences](#non-morphological_features_sentences) subset:
+  ```python
+  from datasets import load_dataset
+  knesset_corpus = load_dataset("HaifaCLGroup/knessetCorpus", name="no_morph_all_features_sentences")
+  
+  ```
+  See [Subsets](#subsets) for other subsets options and change the name field accordingly.
+
+
+#### Option 2: ElasticSearch
+IP address, username and password for the es server and [Kibana](http://34.0.64.248:5601/)
+ ```python
+  elastic_ip = '34.0.64.248:9200'
+  kibana_ip = '34.0.64.248:5601'
+```
+```python
+  es_username = 'user'
+  es_password = 'knesset'
+ ```
+ ```python
+  es = Elasticsearch(f'http://{elastic_ip}',http_auth=(es_username, es_password), timeout=100)
+  resp = es.search(index="all_features_sentences", body={"query":{"match_all": {}}})
+  print("Got %d Hits:" % resp['hits']['total']['value'])
+  for hit in resp['hits']['hits']:
+      print("id: %(sentence_id)s: speaker_name: %(speaker_name)s: sentence_text: %(sentence_text)s" % hit["_source"])
+ ```
+
+#### Option 3: Directly from files
+ ```python
+  import json
+
+  path = <path to committee_full_sentences.jsonl> #or any other sentences jsonl file
+  with open(path, encoding="utf-8") as file:
+    for line in file:
+        try:
+            sent = json.loads(line)
+        except Exception as e:
+            print(f'couldnt load json line. error:{e}.')
+        sent_id = sent["sentence_id"]
+        sent_text = sent["sentence_text"]
+        speaker_name = sent["speaker_name"]
+        print(f"ID: {sent_id}, speaker name: {speaker_name},  text: {sent_text")
+  
+  ```
+
 ## Subsets
 
-#### ALL Features Sentences
-- `Name`: "all_features_sentences"
-- `Description`: Samples of all the sentences in the corpus (plenary and committee) together with all the features available in the dataset.      
+#### ALL_Features_Sentences
+- `name`: "all_features_sentences"
+- `description`: Samples of all the sentences in the corpus (plenary and committee) together with all the features available in the dataset.      
 The fields are consistent with the [All Features Sentence](#all_features_sentence) entity.   
 - `Number of examples`: 32,832,205
 - `Data_urls`:   
   ["https://huggingface.co/datasets/HaifaCLGroup/KnessetCorpus/resolve/main/protocols_sentences/committee_full_sentences.jsonl.bz2",
   "https://huggingface.co/datasets/HaifaCLGroup/KnessetCorpus/resolve/main/protocols_sentences/plenary_full_sentences.jsonl.bz2"]
 
-#### Non-Morphological Features Sentences
-- `Name`: "no_morph_all_features_sentences"
-- `Description`: The same as [All Features Sentences](#all_features_sentences) but without the morphological_fields features.    
+#### Non-Morphological_Features_Sentences
+- `name`: "no_morph_all_features_sentences"
+- `description`: The same as [All Features Sentences](#all_features_sentences) but without the morphological_fields features.    
   Ideal if morpho-syntactic annotations aren't relevant to your work, providing a less disk space heavy option.
 - `Number of examples`: 32,832,205
 - `Data_urls`:   
@@ -61,37 +116,37 @@ The fields are consistent with the [All Features Sentence](#all_features_sentenc
   "https://huggingface.co/datasets/HaifaCLGroup/KnessetCorpus/resolve/main/protocols_sentences/plenary_full_sentences.jsonl.bz2"]
 
 #### KnessetMembers
-- `Name`: "knessetMembers"
-- `Description`: samples of the knesset members in the dataset and their meta-data information such as name, gender and factions affiliations.   
+- `name`: "knessetMembers"
+- `description`: samples of the knesset members in the dataset and their meta-data information such as name, gender and factions affiliations.   
 The fields are consistent with the [Person](#person) entity.   
 - `Number of examples`: 1,100
 - Data_urls:["https://huggingface.co/datasets/HaifaCLGroup/KnessetCorpus/raw/main/all_knesset_members_jsons.jsonl"]
 
 #### Factions
-- `Name`: "factions"
-- `Description`: Samples of all the factions in the dataset and their meta-data information such as name, political orientation and active periods.   
+- `name`: "factions"
+- `description`: Samples of all the factions in the dataset and their meta-data information such as name, political orientation and active periods.   
 The fields are consistent with the [Faction](#faction) entity.   
 - `Number of examples`: 153
 - Data_urls:["https://huggingface.co/datasets/HaifaCLGroup/KnessetCorpus/raw/main/factions_jsons.jsonl"]
 
 #### Protocols
-- `Name`: "protocols"
-- `Description`: Samples of the protocols in the dataset and their meta-data information such as date,
+- `name`: "protocols"
+- `description`: Samples of the protocols in the dataset and their meta-data information such as date,
 - knesset number, session name and a list of its sentences.   
 The fields are consistent with the [Protocol](#protocol) entity.   
 - `Number of examples`: 41,319
 - Data_urls:todo
 
 #### Committees ALL Features Sentences
-- `Name`: "committees_all_features_sentences"
-- `Description`: Samples of all the sentences in the committee sessions together with all the features available in the dataset.    
+- `name`: "committees_all_features_sentences"
+- `description`: Samples of all the sentences in the committee sessions together with all the features available in the dataset.    
 The fields are consistent with the [All Features Sentence](#all_features_sentence) entity.   
 - `Number of examples`: 24,805,925
 - Data_urls: ["https://huggingface.co/datasets/HaifaCLGroup/KnessetCorpus/resolve/main/protocols_sentences/committee_full_sentences.jsonl.bz2"]
 
 #### Plenary ALL Features Sentences
-- `Name`: "plenary_all_features_sentences"
-- `Description`: Samples of all the sentences in the plenary sessions together with all the features available in the dataset.    
+- `name`: "plenary_all_features_sentences"
+- `description`: Samples of all the sentences in the plenary sessions together with all the features available in the dataset.    
 The fields are consistent with the [All Features Sentence](#all_features_sentence) entity.   
 - `Number of examples`: 24,805,925
 - Data_urls: ["https://huggingface.co/datasets/HaifaCLGroup/KnessetCorpus/resolve/main/protocols_sentences/plenary_full_sentences.jsonl.bz2"]
@@ -103,9 +158,10 @@ The fields are consistent with the [All Features Sentence](#all_features_sentenc
 [Person](#person) models.    
 - `raw_data`: All the original protocols as recieved from the Knesset in .doc, .docx and pdf formats.
 
-# * All the dates in the dataset are represented in the format: '%Y-%m-%d %H:%M'
 
-## Dataset Entities
+## Dataset Entities and Fields
+### * All the dates in the dataset are represented in the format: '%Y-%m-%d %H:%M'
+
 #### Person
 The Person entity contains the following fields:
 - `person_id`: A unique identifier for the person. For example, "2660". (type: string).
@@ -217,15 +273,7 @@ Please refer to the respective entity section for details on each field.
 
 
 
-## Usage
-
-#### Option 1: with HuggingFace
-
-#### Option 2: with ElasticSearch
-
-#### Option 3: direct from files
 
-<!-- Address questions around how the dataset is intended to be used. -->
 
 ### License