Merge pull request #156 from informagi/hello_world

Add hello world example to readme

README.md

@@ -41,6 +41,42 @@ ed_result = requests.post(API_URL, json={
 }).json()
 ```
 
+## Using REL as a Python package
+
+You can also use REL as a Python package. See the *hello world* example below for how to get started. For more examples, have a look at the [documentation](https://rel.readthedocs.io/en/latest/tutorials/).
+
+```pycon
+from REL.mention_detection import MentionDetection
+from REL.utils import process_results
+from REL.entity_disambiguation import EntityDisambiguation
+from REL.ner import Cmns, load_flair_ner
+
+wiki_version = "wiki_2014"
+base_url = "C:/path/to/rel_data"
+
+input_text = {
+    "my_doc": ("Hello, world!", []),
+}
+
+mention_detection = MentionDetection(base_url, wiki_version)
+tagger_ner = load_flair_ner("ner-fast")
+
+tagger_ngram = Cmns(base_url, wiki_version, n=5)
+mentions, n_mentions = mention_detection.find_mentions(input_text, tagger_ngram)
+
+config = {
+    "mode": "eval",
+    "model_path": "ed-wiki-2014",
+}
+model = EntityDisambiguation(base_url, wiki_version, config)
+
+predictions, timing = model.predict(mentions)
+result = process_results(mentions, predictions, input_text)
+print(result)
+# {'my_doc': [(0, 13, 'Hello, world!', 'Hello_world_program', 0.6534378618767961, 182, '#NGRAM#')]}
+```
+
+
 ## Installation
 
 This section describes how to deploy REL on a local machine and setup the API. If you want to do anything more than simply running our API locally, you can skip the Docker steps and continue with installation from source.

docs/tutorials/e2e_entity_linking.md

@@ -105,7 +105,7 @@ from REL.entity_disambiguation import EntityDisambiguation
 from REL.ner import Cmns, load_flair_ner
 
 wiki_version = "wiki_2014"
- ```
+```
 
 The code below serves as an example as to how users should format their dataset. This should obviously be replaced
 and should not be used in production, although the outcome is the `input_text` variable that will be used throughout this