A brief history of natural logic

By J. Benthem. 2008

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In Natural Language Processing

Citations in the corpus

A Decomposable Attention Model for Natural Language Inference (2016, background): “NLI is a central problem in language understanding (Katz, 1972; Bos and Markert, 2005; van Benthem, 2008; MacCartney and Manning, 2009) and recently the large SNLI corpus of 570K sentence pairs was created for this task (Bowman et al., 2015).”
A large annotated corpus for learning natural language inference (2015, background): “The semantic concepts of entailment and contra-diction are central to all aspects of natural language meaning (Katz, 1972; van Benthem, 2008), from the lexicon to the content of entire texts.”
Dynabench: Rethinking Benchmarking in NLP (2021, background): “Built upon the semantic foundation of natural logic (Sánchez Valencia, 1991, i.a.) and hailing back much further (van Benthem, 2008), NLI is one of the quintessential natural language understanding tasks.”
NaturalLI: Natural Logic Inference for Common Sense Reasoning (2014, background): “The logic builds upon traditional rather than first-order logic: to a first approximation, Natural Logic can be seen as an enhanced version of Aristotle’s syllogistic system (van Benthem, 2008).”
Causal Abstractions of Neural Networks (2021, methodology): “This challenging dataset was constructed with a tree-structured natural logic causal model [17, 29, 14].”
Leveraging Linguistic Structure For Open Domain Information Extraction (2015, background): “For a more comprehensive introduction to natural logic, see van Benthem (2008).”
A Neural Architecture Mimicking Humans End-to-End for Natural Language Inference (2016, background): “NLI is one of the most important component for natural language understanding systems [Benthem, 2008; MacCartney and Manning, 2009].”
A Natural Proof System for Natural Language (2017, background): “8For a brief history of natural logic see van Benthem (2008a).”
Adversarially Regularising Neural NLI Models to Integrate Logical Background Knowledge (2018, background): “…et al., 2000; Condoravdi et al., 2003; Dagan et al., 2005), is a central problem in language understanding (Katz, 1972; Bos and Markert, 2005; van Benthem, 2008; MacCartney and Manning, 2009), and thus it is especially well suited to serve as a benchmark task for research in machine reading.”