Mondeca VAGO Demo

VAGO: VAGUE VS PRECISE ANALYZER

Need to know if content is vague or not? Then let VAGO analyze it for you. Vago uses an NLP semantic engine to identify vague sentences and explain why!

VAGO highlights the first results of the Disinformation project 'DIEKB' that started in June 2019 and which is funded by the French Direction Générale de l'Armement (DGA). The DIEKB project is a consortium led by Mondeca and involving the Institut Jean-Nicod (CNRS/EHESS/ENS, PSL University, P. Egré & B. Icard) as a research partner, and Airbus Defense & Space as an industrial partner. Here is the link to the R&D project it originated from (DIEKB project).

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How it works

Have a look at a schematic description of the process here.

Submit any textual content to the Mondeca Vagueness Analyzer (also supports API calls).

Your texts are classified by our semantic analyzer. The analyzer uses a configurable ontology-based NLP engine.

The result lists vague vs. precise sentences and the different types of vague terms are evidenced.

and the different types of vague terms are evidenced.

Vague or Precise?

Results summary:

VAGUE PRECISE

OPINION FACTUAL

Results details:

Sentence	Vagueness triggers, by type

Vagueness types

Generality	Under-specific elements in language. e.g., Zoe invited some friends yesterday
Approximation	Coarse-grained expressions used in language which accept a larger range of interpretations than its literal meaning. e.g., Few presidents have been elected at around 40 years old like Emmanuel Macron
Degree	Quantitative indeterminacy attached to gradable expressions. e.g., There are many participants in the meeting
Combinatory	Coexistence of many possible meanings for a word or phrase (polysemy and multidimensionality). e.g., This chocolate is healthy

How to read the barometers?

Vague:	a sentence expressing underspecified, approximate, or uncertain information
Precise:	a sentence containing no marker of vagueness.
Opinion:	a sentence containing markers of subjectivity
Factual:	a sentence containing no markers of subjectivity

What's the point of looking for vagueness in text or speech?

Precision: the quality of being exact, accurate and careful (Oxford Languages), often a marker of factuality.
Vagueness: the lack of certainty or distinctness (Oxford Languages), often a marker of subjectivity.

Vagueness ratings will be combined with other types of ratings, such as credibility ratings of the source or the author, and support the broader scope of identifying disinformation or fake news. This is where we are going in the next steps of this project.