Project Details
Description
In many situations it is required to analyze textual information to answer questions.
When this cannot be done through the similarity between the question and some fragment of the text, it is necessary to perform common sense reasoning based on domain information to infer a possible answer.
In this context, it is very relevant to have a tool that can answer these questions automatically.
For example:
Text: Juan and Pablo took a plane from Bogotá to Cartagena.
The plane made a stopover in Medellín, where Juan was arrested.
Questions:
Where is Pablo at the end of this journey?
Where is Juan at the end of this journey?
Where is the plane at the end of this trip?
When this cannot be done through the similarity between the question and some fragment of the text, it is necessary to perform common sense reasoning based on domain information to infer a possible answer.
In this context, it is very relevant to have a tool that can answer these questions automatically.
For example:
Text: Juan and Pablo took a plane from Bogotá to Cartagena.
The plane made a stopover in Medellín, where Juan was arrested.
Questions:
Where is Pablo at the end of this journey?
Where is Juan at the end of this journey?
Where is the plane at the end of this trip?
Layman's description
In many situations it is required to analyze textual information to answer questions.
When this cannot be done through the similarity between the question and some fragment of the text, it is necessary to perform common sense reasoning based on domain information to infer a possible answer.
In this context, it is very relevant to have a tool that can answer these questions automatically.
For example:
Text: Juan and Pablo took a plane from Bogotá to Cartagena.
The plane made a stopover in Medellín, where Juan was arrested.
Questions:
Where is Pablo at the end of this journey?
Where is Juan at the end of this journey?
Where is the plane at the end of this trip?
Where would Juan be if he hadn't been arrested?
When this cannot be done through the similarity between the question and some fragment of the text, it is necessary to perform common sense reasoning based on domain information to infer a possible answer.
In this context, it is very relevant to have a tool that can answer these questions automatically.
For example:
Text: Juan and Pablo took a plane from Bogotá to Cartagena.
The plane made a stopover in Medellín, where Juan was arrested.
Questions:
Where is Pablo at the end of this journey?
Where is Juan at the end of this journey?
Where is the plane at the end of this trip?
Where would Juan be if he hadn't been arrested?
Keywords
Natural language formalization, automatic reasoning, knowledge representation, artificial intelligence.
Commitments / Obligations
•A minimally viable prototype of a tool that allows answering questions that involve common sense reasoning about a text from a particular domain, with some restrictions on the type of Spanish phrases that the tool is capable of processing.
•A research article to be presented in international indexing journals.
•A research article to be presented in international indexing journals.
| Short title | A semantic analysis tool. |
|---|---|
| Acronym | QA&RA |
| Status | Finished |
| Effective start/end date | 7/11/22 → 7/11/23 |
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
Main Funding Source
- Installed Capacity (Academic Unit)
Location
- Bogotá D.C.
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