About the API standards
Wikimeta semantic labeling web service provides a fully REST compliant unique access point for all text-mining and content analysis functionality.
The API url is [www.wikimeta.com/wapi/service].
You can ask either JSON or XML format in a standard REST accept header.
You then use POST to transmit text content in the "contenu" field and your API account key in the "api" field.
API Access Key
To use Wikimeta API, you need an access key. If you do not have an API key, you must first obtain one. This is done instantly: open your Wikimeta API account
and obtain your key online in a second. Your account will give you access to extra semantic services, like the semantic html editor
API Usage Quotas
Currently, the API default free usage quotas are 100 calls and 1 megabyte of data a day. If you need a larger quota, please visit our commercial offers
or contact us
and we would be happy to talk.
Please note that the full access to our webservice (no quota), with a bandwith of 60 kbytes / minute is always granted for student work, on simple request.
Sample source code of API caller
Wikimeta API can be easily called from any major programming language: Java, C/C++, C#, Perl, PHP, Python, Ruby, and more! Use our software samples bellow to integrate Wikimeta API into your development project.
Sample in perl Download Perl API caller sample
Sample in python Download Python API caller sample
Sample in Java Download Java API caller sample
Forming a call and optional parameters of the API
Wikimeta REST interface is the simplest and fastest way to submit your documents. Hereâ€™s how you can invoke request with this API.
Clients should define their format as JSON or XML in the REST accept header.
Clients should create an HTTP POST request.
Document content should be passed as POST, in the section "contenu".
Submitted content should be UTF-8 encoded.
Your Wikimeta API key is passed as POST in the section "api"
Different processing and user options can be specified. Specification of all other options is optional.
Span value give the amount of word context used for disambiguation.
Force the language model used (FRench, ENglish or SPanish). This is useful when a short text sequence is not sufficient to activate the detection function (default EN).
0 parameter activate Named Entity Recognition (NER) only, 1 activate NER and semantic labeling. This is useful if you only need Named Entities labels (3 to 6 time faster).
This option activate the text mining feature. This introduce verbs, adjective and words frequence count. 0 is default option.