Textual Analogy Parsing
2 papers with code • 0 benchmarks • 0 datasets
Textual Analogy Parsing (TAP) is the task of identifying analogy frames from text.
( Image credit: Textual Analogy Parsing: What’s Shared and What’s Compared among Analogous Facts )
Benchmarks
These leaderboards are used to track progress in Textual Analogy Parsing
Most implemented papers
Textual Analogy Parsing: What's Shared and What's Compared among Analogous Facts
mrlamm/textual-analogy-parsing
•
•
EMNLP 2018
To understand a sentence like "whereas only 10% of White Americans live at or below the poverty line, 28% of African Americans do" it is important not only to identify individual facts, e. g., poverty rates of distinct demographic groups, but also the higher-order relations between them, e. g., the disparity between them.
Life is a Circus and We are the Clowns: Automatically Finding Analogies between Situations and Processes
Analogy-making gives rise to reasoning, abstraction, flexible categorization and counterfactual inference -- abilities lacking in even the best AI systems today.
