This project has received funding from the European Union’s Seventh
Framework Programme for research, technological development and
demonstration under grant agreement no 261712.
This module implements a tagger for hotel properties for Dutch, English, French, Italian, Spanish and German. It detects aspect words, for instance words related with “room”, “cleanliness”, “staff” or “breakfast” and links them with the correct aspect class. The input for this module has to be a valid KAF file with at lest the term layer, as the lemmas will be used for detecting the hotel properties. The output is also a KAF valid file extended with the property layer. This module works for all the languages within the OpeNER project (en,de,nl,fr,es,it) and the language is read from the input KAF file, from the lang attribute of the KAF element (make sure your preprocessors set properly this value or you might use the resources for a wrong language)
This software is part of a larger collection of natural language processing tools known as “the OpeNER project”. You can find more information about the project at the OpeNER portal. There you can also find references to terms like KAF (an XML standard to represent linguistic annotations in texts), component, cores, scenario’s and pipelines.
Keep in mind that this component uses PYTHON so it’s advised to make sure you have a virtualenv activated before installing.
Installing the property-tagger can be done by executing:
gem install opener-property-tagger
Please keep in mind that all components in OpeNER take KAF as an input and output KAF by default.
You should now be able to call the property tagger as a regular shell command: by its name. Once installed the gem normally sits in your path so you can call it directly from anywhere.
This application reads a text from standard input in order process it.
cat some_kind_of_kaf_file.kaf | property-tagger --resource-path /path/to/lexicons/
The property tagger will search in the resource-path for files named {language_code}.txt, for example en.txt.
An excerpt of a potential output would than be:
<features>
<properties>
<property pid="p1" lemma="cleanliness">
<references>
<!--dirty-->
<span>
<target id="t_12"/>
</span>
</references>
</property>
<property pid="p2" lemma="sleeping_comfort">
<references>
<!--bed-->
<span>
<target id="t_10"/>
</span>
</references>
</property>
<property pid="p3" lemma="staff">
<references>
<!--staff-->
<span>
<target id="t_16"/>
</span>
<!--friendly-->
<span>
<target id="t_20"/>
</span>
</references>
</property>
</properties>
</features>
You can launch a webservice by executing:
property-tagger-server --resource-path /path/to/resources
This will launch a mini webserver with the webservice. It defaults to port 9292, so you can access it at http://localhost:9292.
To launch it on a different port provide the -p [port-number] option like this:
property-tagger-server -p 1234
It then launches at http://localhost:1234
Documentation on the Webservice is provided by surfing to the urls provided above. For more information on how to launch a webservice run the command with the -h option.
Last but not least the property tagger comes shipped with a daemon that can read jobs (and write) jobs to and from Amazon SQS queues. For more information type:
property-tagger-daemon -h
This component runs best if you run it in an environment suited for OpeNER components. You can find an installation guide and helper tools in the OpeNER installer and aninstallation guide on the Opener Website
At least you need the following system setup:
The lexicons in the resource path must be stored in a file and follow this format:
shell
surf verb facilities
surfer noun facilities
surfing verb facilities
So, one aspect per line, with 3 fields separated by a tabulator, the first one is the word or span of words (in this case use whitespaces), then the part of speech (which actually it is not use, you can include a dummy label) and finally the aspect class associated with the word.
The component is a fat wrapper around the actual language technology core. You can find the core technolies (python) in the /core directory.
If you encounter problems, please email support@opener-project.eu or leave an issue in the issue tracker.
git checkout -b my-new-feature)git commit -am 'Add some feature')git push origin my-new-feature)This application reads a text from standard input in order process it.
cat some_kind_of_kaf_file.kaf | property-tagger --resource-path /path/to/lexicons/
The property tagger will search in the resource-path for files named {language_code}.txt, for example en.txt.
An excerpt of a potential output would than be:
<features>
<properties>
<property pid="p1" lemma="cleanliness">
<references>
<!--dirty-->
<span>
<target id="t_12"/>
</span>
</references>
</property>
<property pid="p2" lemma="sleeping_comfort">
<references>
<!--bed-->
<span>
<target id="t_10"/>
</span>
</references>
</property>
<property pid="p3" lemma="staff">
<references>
<!--staff-->
<span>
<target id="t_16"/>
</span>
<!--friendly-->
<span>
<target id="t_20"/>
</span>
</references>
</property>
</properties>
</features>
You can also download resources on the fly at boot time. This is particularly interesting when launching a daemon or webservice, but it might also be useful from the command line.
When given the --resource-url option the software will download the file given (.zip or .tar.gz) into the /tmp folder and extract it into the resource-path folder. Subsequently it will use that resource-path to do its work.
If the resource has been downloaded before, and it is detected that the downloaded file is the same as the file on the url location, it will not download the file again, but will simply re-extract the file.
cat some-kind-of-kaf.kaf | property-tagger \
--resource-path ~/resources/property-tagger \
--resource-url http://some.location.com/property-lexicons.zip
You can launch a webservice by executing:
property-tagger-server --resource-path /path/to/resources
After launching the server, you can reach the webservice at http://localhost:9292.
The webservice takes several options that get passed along to Puma, the webserver used by the component. The options are:
-b, --bind URI URI to bind to (tcp://, unix://, ssl://)
-C, --config PATH Load PATH as a config file
--control URL The bind url to use for the control server
Use 'auto' to use temp unix server
--control-token TOKEN The token to use as authentication for the control server
-d, --daemon Daemonize the server into the background
--debug Log lowlevel debugging information
--dir DIR Change to DIR before starting
-e, --environment ENVIRONMENT The environment to run the Rack app on (default development)
-I, --include PATH Specify $LOAD_PATH directories
-p, --port PORT Define the TCP port to bind to
Use -b for more advanced options
--pidfile PATH Use PATH as a pidfile
--preload Preload the app. Cluster mode only
--prune-bundler Prune out the bundler env if possible
-q, --quiet Quiet down the output
-R, --restart-cmd CMD The puma command to run during a hot restart
Default: inferred
-S, --state PATH Where to store the state details
-t, --threads INT min:max threads to use (default 0:16)
--tcp-mode Run the app in raw TCP mode instead of HTTP mode
-V, --version Print the version information
-w, --workers COUNT Activate cluster mode: How many worker processes to create
--tag NAME Additional text to display in process listing
-h, --help Show help
The daemon has the default OpeNER daemon options. Being:
Usage: property-tagger-daemon <start|stop|restart> [options]
When calling property-tagger without <start|stop|restart> the daemon will start as a foreground process
Daemon options:
-i, --input QUEUE_NAME Input queue name
-o, --output QUEUE_NAME Output queue name
--batch-size COUNT Request x messages at once where x is between 1 and 10
--buffer-size COUNT Size of input and output buffer. Defaults to 4 * batch-size
--sleep-interval SECONDS The interval to sleep when the queue is empty (seconds)
-r, --readers COUNT number of reader threads
-w, --workers COUNT number of worker thread
-p, --writers COUNT number of writer / pusher threads
-l, --logfile, --log FILENAME Filename and path of logfile. Defaults to STDOUT
-P, --pidfile, --pid FILENAME Filename and path of pidfile. Defaults to /var/run/tokenizer.pid
--pidpath DIRNAME Directory where to put the PID file. Is Overwritten by --pid if that option is present
--debug Turn on debug log level
--relentless Be relentless, fail fast, fail hard, do not continue processing when encountering component errors
These daemons make use of Amazon SQS queues and other Amazon services. The access to these services and other environment variables can be configured using a .opener-daemons-env file in the home directory of the current user.
It is also possible to provide the environment variables directly to the deamon.
For example:
AWS_REGION='eu-west-1' property-tagger start [other options]
We advise to have the following environment variables available:
That depends on your lexicons. The project will soon open up News lexicons for the following languages:
This project has received funding from the European Union’s Seventh
Framework Programme for research, technological development and
demonstration under grant agreement no 261712.