Linguistic Fundamentals for Natural Language Processing II: 100 Essentials from Semantics and Pragmatics

By Emily M. Bender, Alex Lascarides. 2019

30 citations recorded by the source corpus.

Abstract Meaning is a fundamental concept in Natural Language Processing (NLP), in the tasks of both Natural Language Understanding (NLU) and Natural Language Generation (NLG). This is because the ...

Subfields: Artificial Intelligence, Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Ben Hutchinson
2. Vinodkumar Prabhakaran
3. Dong Nguyen
4. Jason Baldridge
5. Gary F. Marcus
6. Hector Geffner
7. Efstathios Stamatatos
8. Mohit Bansal

In Natural Language Processing

1. Ben Hutchinson
2. Jason Baldridge
3. Dong Nguyen
4. Gary F. Marcus
5. Vinodkumar Prabhakaran
6. D. Gunning

Citations in the corpus

• The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence (2020, background): “Where are my clothes), you need an internal model of the world, and a way of updating that model over time, a process some linguists refer to as discourse update (Bender & Lascarides, 2019).”
• Underspecification in Scene Description-to-Depiction Tasks (2022, methodology): “…here reflects how it has been used in NLP literature, referring both to ambiguity in the objects of study (e.g., linguistic forms (Bender and Lascarides, 2019, p. 29)), as well as to properties of the technical apparatus used to model meaning (e.g., Bender and Lascarides 2019, p. 30).”
• On learning and representing social meaning in NLP: a sociolinguistic perspective (2021, background): “Text data may already allow models to pick up patterns associated with social meaning, as Bender and Lascarides (2019, p.20) note about social meaning that ‘ it is (partly) derivable from form ’.”