echo 'Wow, superTool!;)' | somajo-tokenizer -c -
Wow
,
super
Tool
!
;)
SoMaJo is a rule-based tokenizer and sentence splitter that implements tokenization guidelines for German and English. It has a strong focus on web and social media texts (it was originally created as the winning submission to the EmpiriST 2015 shared task on automatic linguistic annotation of computer-mediated communication / social media) and is particularly well-suited to perform tokenization on all kinds of written discourse, for example chats, forums, wiki talk pages, tweets, blog comments, social networks, SMS and WhatsApp dialogues. Of course it also works on more formal texts.
Version 1 of the tokenizer is described in greater detail in Proisl and Uhrig (2016).
For part-of-speech tagging (in particular of German web and social media texts), we recommend SoMeWeTa:
somajo-tokenizer --split_sentences <file> | somewe-tagger --tag <model> -
- Rule-based tokenization and sentence-splitting:
- EmpiriST 2015 tokenization guidelines for German
- “New” Penn Treebank conventions for English (described, for example, in the guidelines for ETTB 2.0 (Mott et al., 2009) and CLEAR (Warner et al., 2012))
- Optionally split camel-cased tokens
- Optionally output token class information for each token, i.e. if it is a number, an emoticon, an abbreviation, etc.
- Optionally output additional information for each token, e.g. if it was followed by whitespace or if it contained internal whitespace
- Optionally split the tokenized text into sentences
- Optionally determine the character offsets of the tokens in the input, allowing for stand-off tokenization
- Text preprocessing/cleaning:
- Normalize text to Unicode Normalization Form C (NFC)
- Remove control characters and other usually unwanted characters, such as soft hyphens and zero-width spaces
- XML support:
- Transparent processing of XML: Tokenize the textual content of an XML file while preserving the XML structure
- Optionally delimit sentence boundaries by XML tags
- Optionally prune tags, i.e. subtrees, from the XML before
tokenization (for example to remove
<script>and<style>tags from HTML input) - Optionally strip all tags from the output, effectively turning the XML into plain text
- Parallelization: Optionally run multiple worker processes to speed up tokenization
SoMaJo can be easily installed using pip (pip3 in some distributions):
pip install -U SoMaJoAlternatively, you can download and decompress the latest release or clone the git repository:
git clone https://github.com/tsproisl/SoMaJo.gitIn the new directory, run the following command:
pip install -U .You can use the tokenizer as a standalone program from the command
line. General usage information is available via the -h option:
somajo-tokenizer -h
usage: somajo-tokenizer [-h] [-l {en_PTB,de_CMC}]
[-s {single_newlines,empty_lines}] [-x] [--tag TAG]
[--prune PRUNE] [--strip-tags] [-c]
[--split_sentences] [--sentence_tag SENTENCE_TAG] [-t]
[-e] [--parallel N] [-v]
FILE
A tokenizer and sentence splitter for German and English texts. Currently, two
tokenization guidelines are implemented: The EmpiriST guidelines for German
web and social media texts (de_CMC) and the "new" Penn Treebank conventions
for English texts (en_PTB).
positional arguments:
FILE The input file (UTF-8-encoded) or "-" to read from
STDIN.
options:
-h, --help show this help message and exit
-l {en_PTB,de_CMC}, --language {en_PTB,de_CMC}
Choose a language. Currently supported are German
EmpiriST-style tokenization (de_CMC) and English Penn-
Treebank-style tokenization(en_PTB). (Default: de_CMC)
-s {single_newlines,empty_lines}, --paragraph_separator {single_newlines,empty_lines}
How are paragraphs separated in the input text? Will
be ignored if option -x/--xml is used. (Default:
empty_lines)
-x, --xml The input is an XML file. You can specify tags that
always constitute a sentence break (e.g. HTML p tags)
via the --tag option.
--tag TAG Start and end tags of this type constitute sentence
breaks, i.e. they do not occur in the middle of a
sentence. Can be used multiple times to specify
multiple tags, e.g. --tag p --tag br. Implies option
-x/--xml. (Default: --tag title --tag h1 --tag h2
--tag h3 --tag h4 --tag h5 --tag h6 --tag p --tag br
--tag hr --tag div --tag ol --tag ul --tag dl --tag
table)
--prune PRUNE Tags of this type will be removed from the input
before tokenization. Can be used multiple times to
specify multiple tags, e.g. --tag script --tag style.
Implies option -x/--xml. By default, no tags are
pruned.
--strip-tags Suppresses output of XML tags. Implies option
-x/--xml.
-c, --split_camel_case
Split items in written in camelCase (excluding
established names and terms).
--split_sentences, --split-sentences
Also split the input into sentences.
--sentence_tag SENTENCE_TAG, --sentence-tag SENTENCE_TAG
Tag name for sentence boundaries (e.g. --sentence_tag
s). If this option is specified, sentences will be
delimited by XML tags (e.g. <s>…</s>) instead of empty
lines. This option implies --split_sentences
-t, --token_classes Output the token classes (number, XML tag,
abbreviation, etc.) in addition to the tokens.
-e, --extra_info Output additional information for each token:
SpaceAfter=No if the token was not followed by a space
and OriginalSpelling="…" if the token contained
whitespace.
--character-offsets Output character offsets in the input for each token.
--parallel N Run N worker processes (up to the number of CPUs) to
speed up tokenization.
-v, --version Output version information and exit.
Here are some common use cases:
-
To tokenize a text file according to the guidelines of the EmpiriST 2015 shared task:
somajo-tokenizer -c <file>Show example
echo 'der beste Betreuer? - >ProfSmith! : )' | somajo-tokenizer -c - der beste Betreuer ? -> Prof Smith ! :) -
If you do not want to split camel-cased tokens, simply drop the
-coption:somajo-tokenizer <file>Show example
echo 'der beste Betreuer? - >ProfSmith! : )' | somajo-tokenizer - der beste Betreuer ? -> ProfSmith ! :) -
Your input delimits paragraphs by single newlines instead of empty lines? Tell the tokenizer via the
-s/--paragraph_separatoroption:somajo-tokenizer --paragraph_separator single_newlines <file> -
In addition to tokenizing the input, SoMaJo can also split it into sentences:
somajo-tokenizer --split-sentences <file>Show example
echo 'Palim, Palim! Ich hätte gerne eine Flasche Pommes Frites.' | somajo-tokenizer --split-sentences - Palim , Palim ! Ich hätte gerne eine Flasche Pommes Frites . -
To tokenize English text according to the “new” Penn Treebank conventions, explicitly specify the tokenization guideline using the
-l/--languageoption:somajo-tokenizer -l en_PTB <file>Show example
echo 'Dont you wanna come?' | somajo-tokenizer -l en_PTB - Do nt you wan na come ? -
SoMaJo can also process XML files. Use the
-x/--xmloption to tell the tokenizer that your input is an XML file:somajo-tokenizer --xml <xml-file>Show example
echo '<html><head><title>Weihnachten</title></head><body><p>Früher war mehr Lametta!</p></body></html>' | somajo-tokenizer --xml - <html> <head> <title> Weihnachten </title> </head> <body> <p> Früher war mehr Lametta ! </p> </body> </html> -
For XML input, you can use (multiple instances of) the
--tagoption to specify XML tags that are always sentence breaks, i.e. that can never occur in the middle of a sentence. See the help message for the default list of tags.somajo-tokenizer --xml --split_sentences --tag h1 --tag p --tag div <xml-file> -
Via option
-t/--token_classes, SoMaJo can output token class information for each token, i.e. if it is a number, an emoticon, an abbreviation, etc. Via option-e/--extra_info, additional information is available, e.g. if a token was followed by whitespace or if it contained internal whitespace.Show example
echo 'der beste Betreuer? - >ProfSmith! : )' | somajo-tokenizer -c -e -t - der regular beste regular Betreuer regular SpaceAfter=No ? symbol -> symbol SpaceAfter=No, OriginalSpelling="- >" Prof regular SpaceAfter=No Smith regular SpaceAfter=No ! symbol :) emoticon OriginalSpelling=": )" -
To speed up tokenization, you can specify the number of worker processes used via the
--paralleloption:somajo-tokenizer --parallel <number> <file>
Take a look at the API documentation.
You can incorporate SoMaJo into your own Python projects. All you need
to do is importing somajo, creating a SoMaJo object and calling
one of its tokenizer functions: tokenize_text, tokenize_text_file,
tokenize_xml or tokenize_xml_file. These functions return a
generator that yields tokenized chunks of text. By default, these
chunks of text are sentences. If you set split_sentences=False, then
the chunks of text are either paragraphs or chunks of XML. Every
tokenized chunk of text is a list of Token objects.
Here is an example for tokenizing and sentence splitting two paragraphs:
from somajo import SoMaJo
tokenizer = SoMaJo("de_CMC", split_camel_case=True)
# note that paragraphs are allowed to contain newlines
paragraphs = ["der beste Betreuer?\n-- ProfSmith! : )",
"Was machst du morgen Abend?! Lust auf Film?;-)"]
sentences = tokenizer.tokenize_text(paragraphs)
for sentence in sentences:
for token in sentence:
print(f"{token.text}\t{token.token_class}\t{token.extra_info}")
print()And here is an example for tokenizing and sentence splitting a whole
file. The option paragraph_separator="single_newlines" states that
paragraphs are delimited by newlines instead of empty lines:
sentences = tokenizer.tokenize_text_file("Beispieldatei.txt", paragraph_separator="single_newlines")
for sentence in sentences:
for token in sentence:
print(token.text)
print()For processing XML data, use the tokenize_xml or tokenize_xml_file
methods:
eos_tags = ["title", "h1", "p"]
# you can read from an open file object
sentences = tokenizer.tokenize_xml_file(file_object, eos_tags)
# or you can specify a file name
sentences = tokenizer.tokenize_xml_file("Beispieldatei.xml", eos_tags)
# or you can pass a string with XML data
sentences = tokenizer.tokenize_xml(xml_string, eos_tags)
for sentence in sentences:
for token in sentence:
print(token.text)
print()SoMaJo was the system with the highest average F₁ score in the EmpiriST 2015 shared task. The performance of the current version on the two test sets is summarized in the following table (Training and test sets are available from the official website):
| Corpus | Precision | Recall | F₁ |
|---|---|---|---|
| CMC | 99.71 | 99.56 | 99.64 |
| Web | 99.91 | 99.92 | 99.91 |
SoMaJo can also tokenize English text. In general, we follow the “new” Penn Treebank conventions described, for example, in the guidelines for ETTB 2.0 (Mott et al., 2009) and CLEAR (Warner et al., 2012).
For tokenizing English text on the command line, specify the language
via the -l or --language option:
somajo-tokenizer -l en_PTB <file>
From Python, you can pass language="en_PTB" to the SoMaJo
constructor, e.g.:
paragraphs = ["That aint bad!:D"]
tokenizer = SoMaJo(language="en_PTB")
sentences = tokenizer.tokenize_text(paragraphs)Performance of the English tokenizer:
| Corpus | Precision | Recall | F₁ |
|---|---|---|---|
| English Web Treebank | 99.66 | 99.64 | 99.65 |
Here are some brief notes to help you get started:
-
Preferably create a dedicated virtual environment.
-
Make sure you have pip ≥ 21.3.
-
Install the project in editable mode:
pip install -U -e . -
Install the development dependencies:
pip install -r requirements_dev.txt
-
To run the tests:
python3 -m unittest discover
-
To build the documentation:
cd doc make markdownNote that the created markdown is not perfect and needs some manual postprocessing.
-
To build the distribution files:
python3 -m build
If you use SoMaJo for academic research, please consider citing the following paper:
-
Proisl, Thomas, and Peter Uhrig. 2016. “SoMaJo: State-of-the-Art Tokenization for German Web and Social Media Texts.” In Proceedings of the 10th Web as Corpus Workshop (WAC-X) and the EmpiriST Shared Task, edited by Paul Cook, Stefan Evert, Roland Schäfer, and Egon Stemle, 57–62. Berlin: Association for Computational Linguistics. https://doi.org/10.18653/v1/W16-2607.
@InProceedings{Proisl_Uhrig_EmpiriST:2016, author = {Proisl, Thomas and Uhrig, Peter}, title = {{SoMaJo}: {S}tate-of-the-art tokenization for {G}erman web and social media texts}, year = {2016}, booktitle = {Proceedings of the 10th {W}eb as {C}orpus Workshop ({WAC-X}) and the {EmpiriST} Shared Task}, editor = {Cook, Paul and Evert, Stefan and Schäfer, Roland and Stemle, Egon}, address = {Berlin}, publisher = {Association for Computational Linguistics}, pages = {57--62}, doi = {10.18653/v1/W16-2607}, url = {https://aclanthology.org/W16-2607}, }