Social Science Dashboard Specification: a tool for supporting social scientists in their research by using MUHAI technologies

Excerpt2: “The ultimate purpose of social sciences is to furnish causal explanations of classes of observable events, which are, at least in part, generated by individual and collective agency/action.” [1] The aim of a digital assistant for social history research is therefore to support social scientists with the construction of such causal explanations for observable events, also theories or hypotheses. 
meta: MUHAI milestone [M3.1] (VUA, Month 16)
[M3.1] A specification for supporting social scientists in their research by using MUHAI technologies. (VUA) (M16) “The ultimate purpose of the social sciences is to furnish causal...

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Identifying and tracing the entities of a narrative

Excerpt2: It is widely accepted that humans construct narratives to make sense of complex issues in their lives and society. If we want to build machines that are capable of truly understanding such narratives, we need to be able to reliably identify and track the characters and other entities that play a role in a narrative. For example, if a person writes: “The boy likes The Witches. The book was written by Roald Dahl.”
meta: micro-project
AbstractIt is widely accepted that humans construct narratives to make sense of complex issues in their lives and society. If we want to build machines that are capable of truly...

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Scaling Constructional Language Processing: Techniques for Managing Large Search Spaces

Excerpt2: Constructionist approaches to language make use of form-meaning pairings, called constructions, to capture all linguistic knowledge that is necessary for comprehending and producing natural language expressions. Language processing consists then in combining the constructions of a grammar in such a way that they solve a given language comprehension or production problem.
meta: micro-project
AbstractConstructionist approaches to language make use of form-meaning pairings, called constructions, to capture all linguistic knowledge that is necessary for comprehending and...

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Italian Frame Extractor

Excerpt2: The domain of inequality is heavily characterized by causal claims. Multiple researchers in economics, social sciences and humanities have studied the sources of modern inequality. However, modelling their automatic detection in natural language is still an open issue. This research project aims to tackle this gap by detecting explicit causal relationships in Italian texts related to inequality.
meta: micro-project
AbstractCan natural language help to understand the origins and persistence of inequality in our society?The domain of inequality is heavily characterized by causal claims. Multiple...

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Linking Language and Semantic Memory for Building Narratives

Excerpt2: IRL, developed by Luc Steels and collaborators, is a parsing technique that captures the semantics of a natural language expression as a network of logical constraints. Determining the meaning of a sentence then amounts to finding consistent assignments of variables that satisfy these constraints.
meta: micro-project
AbstractIRL, developed by Luc Steels and collaborators, is a parsing technique that captures the semantics of a natural language expression as a network of logical constraints. Determining...

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MUHAI Data Ecosystem

Excerpt2: The main objective of this miniproject is to identify a design solution for MUHAI’s data ecosystem and for the integration of its components. MUHAI, is a project that focuses on human-machine understanding and cooperation, by means of mimicking in machines how humans make sense of experiences.
meta: micro-project
AbstractThe main objective of this miniproject is to identify a design solution for MUHAI’s data ecosystem and for the integration of its components. MUHAI, is a project that focuses...

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951846