pymusas - v0.3.0

What's new

Added 🎉

• Roadmap added.
• Define the MWE template and it's syntax, this is stated in Notes -> Multi Word Expression Syntax in the Usage section of the documentation. This is the first task of issue #24.
• PEP 561 (Distributing and Packaging Type Information) compatible by adding py.typed file.
• Added srsly as a pip requirement, we use srsly to serialise components to bytes, for example the pymusas.lexicon_collection.LexiconCollection.to_bytes function uses srsly to serialise the LexiconCollection to bytes.
• An abstract class, pymusas.base.Serialise, that requires sub-classes to create two methods to_bytes and from_bytes so that the class can be serialised.
• pymusas.lexicon_collection.LexiconCollection has three new methods to_bytes, from_bytes, and __eq__. This allows the collection to be serialised and to be compared to other collections.
• A Lexicon Collection class for Multi Word Expression (MWE), pymusas.lexicon_collection.MWELexiconCollection, which allows a user to easily create and / or load in from a TSV file a MWE lexicon, like the MWE lexicons from the Multilingual USAS repository. In addition it contains the functionality to match a MWE template to templates stored in the MWELexiconCollection class following the MWE special syntax rules, this is all done through the mwe_match method. It also supports Part Of Speech mapping so that you can map from the lexicon's POS tagset to the tagset of your choice, in both a one-to-one and one-to-many mapping. Like the pymusas.lexicon_collection.LexiconCollection it contains to_bytes, from_bytes, and __eq__ methods for serialisation and comparisons.
• The rule based taggers have now been componentised so that they are based off a List of Rules and a Ranker whereby each Rule defines how a token(s) in a text can be matched to a semantic category. Given the matches from the Rules the for each token, a token can have zero or more matches, the Ranker ranks each match and finds the global best match for each token in the text. The taggers now support direct match and wildcard Multi Word Expressions. Due to this:
  • pymusas.taggers.rule_based.USASRuleBasedTagger has been changed and re-named to pymusas.taggers.rule_based.RuleBasedTagger and now only has a __call__ method.
  • pymusas.spacy_api.taggers.rule_based.USASRuleBasedTagger has been changed and re-named to pymusas.spacy_api.taggers.rule_based.RuleBasedTagger.
• A Rule system, of which all rules can be found in pymusas.taggers.rules:
  • pymusas.taggers.rules.rule.Rule an abstract class that describes how other sub-classes define the __call__ method and it's signature. This abstract class is sub-classed from pymusas.base.Serialise.
  • pymusas.taggers.rules.single_word.SingleWordRule a concrete sub-class of Rule for finding Single word lexicon entry matches.
  • pymusas.taggers.rules.mwe.MWERule a concrete sub-class of Rule for finding Multi Word Expression entry matches.
• A Ranking system, of which all of the components that are linked to ranking can be found in pymusas.rankers:
  • pymusas.rankers.ranking_meta_data.RankingMetaData describes a lexicon entry match, that are typically generated from pymusas.taggers.rules.rule.Rule classes being called. These matches indicate that some part of a text, one or more tokens, matches a lexicon entry whether that is a Multi Word Expression or single word lexicon.
  • pymusas.rankers.lexicon_entry.LexiconEntryRanker an abstract class that describes how other sub-classes should rank each token in the text and the expected output through the class's __call__ method. This abstract class is sub-classed from pymusas.base.Serialise.
  • pymusas.rankers.lexicon_entry.ContextualRuleBasedRanker a concrete sub-class of LexiconEntryRanker based off the ranking rules from Piao et al. 2003.
  • pymusas.rankers.lexical_match.LexicalMatch describes the lexical match within a pymusas.rankers.ranking_meta_data.RankingMetaData object.
• pymusas.utils.unique_pos_tags_in_lexicon_entry a function that given a lexicon entry, either Multi Word Expression or Single word, returns a Set[str] of unique POS tags in the lexicon entry.
• pymusas.utils.token_pos_tags_in_lexicon_entry a function that given a lexicon entry, either Multi Word Expression or Single word, yields a Tuple[str, str] of word and POS tag from the lexicon entry.
• A mapping from USAS core to Universal Part Of Speech (UPOS) tagset.
• A mapping from USAS core to basic CorCenCC POS tagset.
• A mapping from USAS core to Penn Chinese Treebank POS tagset tagset.
• pymusas.lexicon_collection.LexiconMetaData, object that contains all of the meta data about a single or Multi Word Expression lexicon entry.
• pymusas.lexicon_collection.LexiconType which describes the different types of single and Multi Word Expression (MWE) lexicon entires and templates that PyMUSAS uses or will use in the case of curly braces.
• The usage documentation, for the "How-to Tag Text", has been updated so that it includes an Indonesian example which does not use spaCy instead uses the Indonesian TreeTagger.
• spaCy registered functions for reading in a LexiconCollection or MWELexiconCollection from a TSV. These can be found in pymusas.spacy_api.lexicon_collection.
• spaCy registered functions for creating SingleWordRule and MWERule. These can be found in pymusas.spacy_api.taggers.rules.
• spaCy registered function for creating ContextualRuleBasedRanker. This can be found in pymusas.spacy_api.rankers.
• spaCy registered function for creating a List of Rules, this can be found here: pymusas.spacy_api.taggers.rules.rule_list.
• LexiconCollection and MWELexiconCollection open the TSV file downloaded through from_tsv method by default using utf-8 encoding.
• pymusas_rule_based_tagger is now a spacy registered factory by using an entry point.
• MWELexiconCollection warns users that it does not support curly braces MWE template expressions.
• All of the POS mappings can now be called through a spaCy registered function, all of these functions can be found in the pymusas.spacy_api.pos_mapper module.
• Updated the Introduction and How-to Tag Text usage documentation with the new updates that PyMUSAS now supports, e.g. MWE's. Also the How-to Tag Text is updated so that it uses the pre-configured spaCy components that have been created for each language, this spaCy components can be found and downloaded from the pymusas-models repository.

Removed 🗑

• pymusas.taggers.rule_based.USASRuleBasedTagger this is now replaced with pymusas.taggers.rule_based.RuleBasedTagger.
• pymusas.spacy_api.taggers.rule_based.USASRuleBasedTagger this is now replaced with pymusas.spacy_api.taggers.rule_based.RuleBasedTagger.
• Using PyMUSAS usage documentation page as it requires updating.

Commits

cc52c6d Added languages that we support a0f748b Merge pull request #32 from UCREL/mwe 5feb6ef Added the changes to the documentation 39b88ae Added link to MWE syntax notes 9b63279 Updated so that it uses the pre-configured models 91a7089 Added that we support MWE and have models that can be downloaded 61b8265 Needs to be updated before being added back into the documentation 4ff95aa version 0.3.0 2ab0d4b Added spacy registered functions for pos mappers 0b288bb Changed API loading page to the base module 6da04a9 MWE Lexicon Collection can handle curly braces being added but will be ignored 5042323 @reader to @misc due to config file format f186803 isort 1e2d045 spacy factory entry point 17f7821 spacy factory entry point 014f73d Added rulelist spacy registered function 37fb15e No longer use OS default encoding 8c21fc8 CI does not fail on windows when it should, Fixed 67ee480 CI does not fail on windows when it should, DEBUGGING e48017a isort 745b57a spacy registered function for ContextualRuleBasedRanker fed00b2 Click issue with version 8.1.0 543b251 spacy registered functions for tagger rules 89d59ec Click issue with version 8.1.0 4b8a22c pytest issue with version 7.1.0 e4b75a5 Click issue with version 8.1.0 787496e spacy registered functions for lexicon collections 6fb5882 Added roadmap link ca53cc6 ROADMAP from main branch 1626496 update 5a98ccd Now up to date 404da49 PEP 561 compatible by adding py.typed file c55d991 Added py.typed 2575138 Added srsly as a requirement bdc84bb Added srsly as a requirement 03ddc79 Moved the newrulebased tagger into rulebased d97aa08 Moved the newrulebased tagger into rulebased 67e60ba flake8 92b43ab Updated examples ea7fd40 Updated examples f2a7d47 Added lexicon TSV file that was deleted after removing old tagger 20ba93b Removed old tagger f316ef5 Serialised methods for custom classes 4135e67 _eq__ methods for the LexiconEntryRanker classes 4ea243b eq methods for the LexiconCollection classes 15a9013 to and from bytes method for the ranker classes 85f96b6 to and from bytes method for SingleWordRule and LexiconCollection 2f1275b Compare meta data directly rather than through a for loop c71c3b5 to and from bytes method for rule and MWE rule 75e341d to and from bytes methods for MWELexiconCollection 8b862e8 Added srsly as known third party package dcd90e0 First version of roadmap e631dd0 ignore abstract method in code coverage results b017816 updatefactoryattributes can update either requires or assigns 0c4b2f2 Corrected docstring 0fe5379 Refactored spacy tagger in doing so created the functions in the utils module 9f4e884 Refactored spacy tagger in doing so created the functions in the utils module 13c2ab3 End of day f74c887 Corrected docstring 4eacbbf Example conll script a4e1f0f Added default punctuation and number POS tags c700642 Added default punctuation and number POS tags fffa4f6 Reverse POS mappers e534ae1 New rule based tagger outputs token indexes of MWE 6f1591b pydoc-markdown requirement fixed b8dd34c Added longestmwetemplate and mostwildcardsinmwetemplate attributes to MWELexiconCollection fa56b3a End of day c17e0f0 make wildcard plural 68b5944 Fixed docstring link error 895e7ee Updated version of the tagger using Rules and Ranker b65da30 MWE Rule match can use a POS Mapper 86c0e6b MWE Rule match can use a POS Mapper 3c4a6f5 MWE lexicon collection can handle POS Mapping f674577 MWE lexicon collection can handle POS Mapping a0fa451 MWE lexicon collection can handle POS Mapping 49f631d removed extra whitespace, flake8 6329d79 removed extra whitespace, flake8 b5c8056 unique pos tags from lexicon entry function cd647db New version of the tagger, works with single word rules e51bbf1 Added pos mapper 62448b3 ContextualRuleBasedRanker works with global lowest ranking b4197dd Refactored test data locations and made tests simpler 65e9828 Restructured single word rule test data 6a15b6b Restructured single word rule test data cc75575 Restructured single word rule test data e929b76 Single word rule 614f0db Corrected docstring ed66305 Corrected docstring 2c43738 Added semantic_tags to RankingMetaData object 2649042 Added MWE Lexicon Rules 7f11774 Added MWE Lexicon Rules 0824a3e Better example 2024873 missing assert statement 1f52680 Test empty list parameter for rule based ranker 2051545 Ranker to rank output from single and MWE rules e57915f Added LexiconMetaData to MWELexiconCollection 526a395 Added Lexicon Meta Data object ee2fe06 Refactored lexicon entry from collection in the tests 0b3b5bc MWE lexicon collection can detect MWE given an MWE template 1e8f7f6 Corrected python examples 5ead038 Documentation 3119906 isort and flake8 corrected and removed an if statement e76c719 Made the MWE direct lookup more efficient 036a85e MWE benchmark for MWE direct lookup 5a8b325 MWE direct lookup can handle regular expression special syntax 99ac3f7 Merge branch 'main' into mwe d381180 Merge pull request #25 from UCREL/indonesian-documentation f597074 Indonesian example added to the usage documentation b765d4b isort issue resolved bf83c87 First version of MWE matching with no special syntax #24 d48656a MWE Lexicon Collection 8823d94 Adds support for raw docstrings 89adf29 Moved LexiconCollection test data into its own folder dc9675e Moved LexiconCollection test data into its own folder dc1f2e3 moved lexicon collection tests into a seperate folder 03d3141 Merge branch 'mwe' of github.com:UCREL/pymusas into mwe 9f1512d Update MWE syntax definitions and examples fc6fbe4 Re-organisation of the test data files/folders 738ff4a Fixed broken link cd1136c Start of the MWE syntax guide

- Python
Published by apmoore1 almost 4 years ago

pymusas - v0.2.0

What's new

Added 🎉

• Release process guide adapted from the AllenNLP release process guide, many thanks to the AllenNLP team for creating the original guide.
• A mapping from the basic CorCenCC POS tagset to USAS core POS tagset.
• The usage documentation, for the "How-to Tag Text", has been updated so that it includes a Welsh example which does not use spaCy instead uses the CyTag toolkit.
• A mapping from the Penn Chinese Treebank POS tagset to USAS core POS tagset.
• In the documentation it clarifies that we used the Universal Dependencies Treebank version of the UPOS tagset rather than the original version from the paper by Petrov et al. 2012.
• The usage documentation, for the "How-to Tag Text", has been updated so that the Chinese example includes using POS information.
• A CHANGELOG file has been added. The format of the CHANGELOG file will now be used for the formats of all current and future GitHub release notes. For more information on the CHANGELOG file format see Keep a Changelog.

Commits

9283107 Changed the publish release part of the instructions fea9510 Prepare for release v0.2.0 5581882 Prepare for release v0.2.0 bd4c74f Prepare for release v0.2.0 3fa0346 Prepare for release v0.2.0 f548e08 Publish to PyPI only on releases rather than tags 85ac891 Merge pull request #23 from UCREL/welsh-example e6efe4a Welsh USAS example e476cde Welsh usage example 854bce6 Merge pull request #22 from UCREL/chinese-pos-tagset-mapping e5e33bf Updated CHANGELOG e6afd2d Corrected English e7b0502 Clarification on UPOS tagset used eab65a6 Changed name from Chinese Penn Treebank to Penn Chinese Treebank aa8dc1d Added Chinese Penn Treebank to USAS core POS mapping 8344730 Updated the Chinese tag-text example to include POS information #19 c726a06 Benchmarking the welsh tagger 4bcc239 Added CHANGELOG file fixes #17 4ad6ab2 Added PyPI downloads badge cf38ff0 Updated to docusaurus version 2.0.0-beta.14 60f0bb5 Updated to latest alpine and node 4b09298 Merge pull request #20 from UCREL/language-documentation c18f092 Alphabetical order d11b332 Portuguese example a7170d7 English syntax mistake d697df9 Spanish example ea601c4 Italian example b7af3b5 French example 6c441b0 Dutch example 01ccf6f position of the sections 547fd08 renamed 77e9a9c Clarification in the introduction a20eac3 Chinese example 0202c5d Added better note formatting 207e023 Merge pull request #16 from UCREL/citation b7299de added RSPM environment variable ae02909 package missing error in Validate-CITATION-cff job 0a5eebf Added sudo f3aeb47 Added citation.cff validator 12e7e65 Citation file and how to validate it 5033c98 Increased version number in preparation for next release df67477 Changed homepage URL and removed bug tracker 414b3a4 Added badges from pypi and changed the emojis

- Python
Published by apmoore1 about 4 years ago

pymusas - v0.1.0 Initial Release

In the initial release we have created a rule based tagger that has been built into different ways:

1. As a spaCy component that can be added to a spaCy pipeline, of which this is called pymusas.spacyapi.taggers.rulebased.USASRuleBasedTagger
2. A non-spaCy version, of which this is called pymusas.taggers.rule_based.USASRuleBasedTagger

In this initial release we have concentrated on building the 1 tagger, the spaCy version, of which all of the usage guides are built around this version of the tagger. However the 2 tagger, non-spaCy version, does work, but has fewer capabilities, e.g. no way of easily saving the tagger to a JSON file etc.

We have also created a LexiconCollection class that allows a user to easily create and / or load in from a TSV file a lexicon, like the single word lexicons from the Multilingual USAS repository. This LexiconCollection can be used to format a lexicon file so that it can be used within the rule based tagger, as shown in the using PyMUSAS tutorial.

Lastly we have created a POS mapping module that contains a mapping between the Universal Part Of Speech (UPOS) tagset and the USAS core POS tagset. This can be used within the spaCy component version of the rule based tagger to convert the POS tags outputted from the spaCy POS model, which use UPOS tagset, to the USAS core tagset, which are used by the single word lexicons from the Multilingual USAS repository. For more information on the use of this mapping feature in the rule based tagger see the using PyMUSAS tutorial

- Python
Published by apmoore1 about 4 years ago