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Glossario IA

Il dizionario completo dell'Intelligenza Artificiale

162
categorie
2.032
sottocategorie
23.060
termini
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Fact Checking

Systematic process of evaluating the veracity of a claim by comparing it to reliable sources and factual data.

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Question-Answering System

Computer application designed to provide accurate answers to questions posed in natural language, based on a knowledge base.

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Evidentiary Proof

Set of sources, citations, or concrete data used by a system to support or refute a given claim.

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Disinformation

Deliberate spread of false or misleading information with the intent to deceive or harm, which QA systems seek to identify.

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Misinformation

Inaccurate information shared without intent to harm, often due to ignorance or misunderstanding, detectable by verification systems.

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Verified Knowledge Base

Structured and validated data corpus serving as a truth reference for a fact-checking question-answering system.

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Contradiction Detection

Mechanism for identifying logical inconsistencies between a claim and information contained in reference sources.

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Subject-Predicate-Object Triplet

Fundamental data structure in information extraction, representing a factual relationship (e.g., 'The Eiffel Tower - is located in - Paris').

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Verifiability

Measure of the degree to which a claim can be confirmed or disproved by external and reliable evidence.

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Reliable Source

Document, website, or database recognized for its accuracy and impartiality, used as a reference for fact verification.

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Evidence Extraction

Technique of isolating relevant sentences or passages in a corpus of documents that support or contradict a claim.

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Veracity Classification

Task of categorizing a claim into predefined classes such as 'True', 'False', 'Mixed', or 'Not verifiable'.

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Stance Detection

Automatic analysis of the position of a text (favorable, unfavorable, or neutral) with respect to a target claim.

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Knowledge Graph

Network of entities and semantic relationships used to model and query real-world facts in a structured manner.

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Multi-source Verification

Approach consisting of cross-referencing information from multiple independent sources to increase the robustness of verification.

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