Category Archives: Text Proofreading

Posts about Text Proofreading

The Text Proofreading API moves to Stilus

Even since the very beginnings of MeaningCloud, we have offered a Text Proofreading API in Spanish which allow you to standardize and ensure the quality of your contents through spelling, grammar and style proofreading.

Stilus logo

On the 2nd of April, we will definitely move this API and its functionality to Stilus, an application where we take advantage of the functionality provided by the API and show everything you can do with it.

To those of you who currently use it, the migration process can be done in three easy steps:

  1. Register at Stilus.
  2. Contact us at support telling us about your volume requirements and which Stilus user would use the API. We will inform you of the conditions and tell you how to subscribe to the API.
  3. Once you have subscribed, you will only have to change the API endpoint and the key parameter value in your integration, and you will be all set to keep using the Text Proofreading API.

If you’d rather use directly the text proofreading functionality online or from Word, check out all the ways in which you can use Stilus!

Migrate from Textalytics: Spellchecker and Language Analysis API

We have just published and updated in MeaningCloud two of the functionalities that were still pending to migrate from Textalytics.

  • Automatic text proofreading checks spelling, grammar and style in your texts for several languages: Spanisn, English, French and Italian.
  • Full language analysis including lemmatization, Part of Speech tagging and syntactic analysis also for several languages. For this API besides English, Spanish, French and Italian we have also Portuguese and Catalan available.

Textalytics users can access MeaningCloud using the same email and password they already had. If you do not remember your password, you can reset and generate a new password.

Developers using Textalytics’ Spell, Grammar and Style Proofreading API or Lemmatization, POS and Parsing API

If you are a user of the following functionalities and want to migrate to MeaningCloud, you can do it already. You only have to:

  1. Update the access point, since the request and response format does not change. Both HTTP and HTTPS endpoints are available.
    API Textalytics MeaningCloud
    Spell, Grammar and Style Proofreading 
    https://textalytics.com/core/stilus-1.2
    		 
    http://api.meaningcloud.com/stilus-1.2
    Lemmatization, POS and Parsing API 
    http://textalytics.com/core/parser-1.2
    		 
    http://api.meaningcloud.com/parser-1.2
  2. Check your license key in MeaningCloud and make sure that you use the correct (and only) license as the value of the parameter ‘license key’ on all requests. You can copy your license key either from the Licenses section in the Account menu, or from the developers home.

As always, if you have doubts or find any other problem, do not hesitate to write us to support@meaningcloud.com. Nevertheless, in order to ensure a smooth transition for client applications all the Textalytics’ API endpoints will be operational until June 1st, 2015.

Use MeaningCloud API with the GATE plug-in

In our attempt to make MeaningCloud API the easiest way to use semantics in your application, today we are proud to present our latest development, a MeaningCloud plug-in for GATE.

GATE (General Architecture for Text Engineering) is an open-source workbench for text engineering that makes use of any kind of language processing component, from document crawling to search, and intelligent semantic annotations in particular.

Benefits for GATE and MeaningCloud API users

The plug-in provides GATE users a new set of multilingual functionalities, from parsing to entity extraction and sentiment analysis. For MeaningCloud users it would mean an easier and quicker method to prototype full applications including crawling, post-processing or indexing on annotated documents.  Besides, if you’re familiar with JAPE rules, it would enable to post-process, mix and match annotations from different processing resources for more complex pipelines. Finally, GATE is ideal for sharing and evaluating pipelines between team members, which increases productivity and produces more accurate results.

Semantic Publishing: a Case Study for the Media Industry

Semantic Publishing at Unidad Editorial: a Client Case Study in the Media Industry 

Last year, the Spanish media group Unidad Editorial deployed a new CMS developed in-house for its integrated newsroom. Unidad Editorial is a subsidiary of the Italian RCS MediaGroup, and publishes some of the newspapers and magazines with highest circulation in Spain, besides owning nation-wide radio stations and a license of DTTV incorporating four TV channels.

Newsroom El Mundo

Newsroom El Mundo

When a journalist adds a piece of news to the system, its content has to be tagged, which constitutes one of the first steps in a workflow that will end with the delivery of this item in different formats, through different channels (print, web, tablet and mobile apps) and for different mastheads. After evaluation of different provider’s solutions in the previous months, the company then decided that semantic tagging would be done through Daedalus’ text analytics technology. Semantic publishing included, in this case, the identification (with disambiguation) of named entities (people, places, organizations, etc.), time and money expressions, concepts, classification according to the IPTC scheme (an international standard for the media industry, with around 1400 classes organized in three levels), sentiment analysis, etc.

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