Update example compatibility statements

examples/information_extraction/entity_relations.py

@@ -6,7 +6,7 @@ money and currency values (entities labelled as MONEY) and then check the
 dependency tree to find the noun phrase they are referring to – for example:
 $9.4 million --> Net income.
 
-Last updated for: spaCy 2.0.0a18
+Compatible with: spaCy 2.0.0a18+
 """
 from __future__ import unicode_literals, print_function
 

examples/information_extraction/parse_subtrees.py

@@ -16,7 +16,7 @@ show you how computers understand [language]
 
 I'm assuming that we can use the token.head to build these groups."
 
-Last updated for: spaCy 2.0.0a18
+Compatible with: spaCy 2.0.0a18+
 """
 from __future__ import unicode_literals, print_function
 

examples/information_extraction/phrase_matcher.py

@@ -33,6 +33,8 @@ formatted in jsonl as a sequence of entries like this:
 {"text":"Annapolis"}
 {"text":"Appalachia"}
 {"text":"Argentina"}
+
+Compatible with: spaCy 2.0.0a17+
 """
 from __future__ import print_function, unicode_literals, division
 

examples/pipeline/custom_attr_methods.py

@@ -7,8 +7,7 @@ they're called on is passed in as the first argument.
 
 * Custom pipeline components: https://alpha.spacy.io//usage/processing-pipelines#custom-components
 
-Developed for: spaCy 2.0.0a17
-Last updated for: spaCy 2.0.0a18
+Compatible with: spaCy 2.0.0a17+
 """
 from __future__ import unicode_literals, print_function
 

examples/pipeline/custom_component_countries_api.py

@@ -8,8 +8,7 @@ coordinates. Can be extended with more details from the API.
 * REST Countries API: https://restcountries.eu (Mozilla Public License MPL 2.0)
 * Custom pipeline components: https://alpha.spacy.io//usage/processing-pipelines#custom-components
 
-Developed for: spaCy 2.0.0a17
-Last updated for: spaCy 2.0.0a18
+Compatible with: spaCy 2.0.0a17+
 """
 from __future__ import unicode_literals, print_function
 

examples/pipeline/custom_component_entities.py

@@ -8,8 +8,7 @@ respectively.
 
 * Custom pipeline components: https://alpha.spacy.io//usage/processing-pipelines#custom-components
 
-Developed for: spaCy 2.0.0a17
-Last updated for: spaCy 2.0.0a18
+Compatible with: spaCy 2.0.0a17+
 """
 from __future__ import unicode_literals, print_function
 

examples/pipeline/multi_processing.py

@@ -6,7 +6,7 @@ each "sentence" on a newline, and spaces between tokens. Data is loaded from
 the IMDB movie reviews dataset and will be loaded automatically via Thinc's
 built-in dataset loader.
 
-Last updated for: spaCy 2.0.0a18
+Compatible with: spaCy 2.0.0a18+
 """
 from __future__ import print_function, unicode_literals
 from toolz import partition_all

examples/training/train_intent_parser.py

@@ -15,8 +15,7 @@ following types of relations: ROOT, PLACE, QUALITY, ATTRIBUTE, TIME, LOCATION.
 ('hotel', 'PLACE', 'show') --> show PLACE hotel
 ('berlin', 'LOCATION', 'hotel') --> hotel with LOCATION berlin
 
-Developed for: spaCy 2.0.0a18
-Last updated for: spaCy 2.0.0a19
+Compatible with: spaCy 2.0.0a20+
 """
 from __future__ import unicode_literals, print_function
 

examples/training/train_ner.py

@@ -7,8 +7,7 @@ For more details, see the documentation:
 * Training: https://alpha.spacy.io/usage/training
 * NER: https://alpha.spacy.io/usage/linguistic-features#named-entities
 
-Developed for: spaCy 2.0.0a18
-Last updated for: spaCy 2.0.0a19
+Compatible with: spaCy 2.0.0a20+
 """
 from __future__ import unicode_literals, print_function
 

examples/training/train_new_entity_type.py

@@ -23,8 +23,7 @@ For more details, see the documentation:
 * Training: https://alpha.spacy.io/usage/training
 * NER: https://alpha.spacy.io/usage/linguistic-features#named-entities
 
-Developed for: spaCy 2.0.0a18
-Last updated for: spaCy 2.0.0a19
+Compatible with: spaCy 2.0.0a20+
 """
 from __future__ import unicode_literals, print_function
 

examples/training/train_parser.py

@@ -5,8 +5,7 @@ model or a blank model. For more details, see the documentation:
 * Training: https://alpha.spacy.io/usage/training
 * Dependency Parse: https://alpha.spacy.io/usage/linguistic-features#dependency-parse
 
-Developed for: spaCy 2.0.0a18
-Last updated for: spaCy 2.0.0a18
+Compatible with: spaCy 2.0.0a20+
 """
 from __future__ import unicode_literals, print_function
 

examples/training/train_tagger.py

@@ -8,8 +8,7 @@ the documentation:
 * Training: https://alpha.spacy.io/usage/training
 * POS Tagging: https://alpha.spacy.io/usage/linguistic-features#pos-tagging
 
-Developed for: spaCy 2.0.0a18
-Last updated for: spaCy 2.0.0a19
+Compatible with: spaCy 2.0.0a20+
 """
 from __future__ import unicode_literals, print_function
 

examples/training/train_textcat.py

@@ -8,8 +8,7 @@ see the documentation:
 * Training: https://alpha.spacy.io/usage/training
 * Text classification: https://alpha.spacy.io/usage/text-classification
 
-Developed for: spaCy 2.0.0a18
-Last updated for: spaCy 2.0.0a19
+Compatible with: spaCy 2.0.0a20+
 """
 from __future__ import unicode_literals, print_function
 import plac

examples/vectors_fast_text.py

@@ -2,6 +2,7 @@
 # coding: utf8
 """Load vectors for a language trained using fastText
 https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md
+Compatible with: spaCy v2.0.0a17+
 """
 from __future__ import unicode_literals
 import plac