Generating Referring Quantified Expressions

In this paper, we describe how quantifiers can be generated in a text generation system. By taking advantage of discourse and ontological information, quantified expressions can replace entities in a text, making the text more fluent and concise. In addition to avoiding ambiguities between distributive and collective readings in universal quantification generation, we will also show how different scope orderings between universal and existential quantifiers will result in different quantified expressions in our algorithm.

• Publication year

  2000

• Venue

  International Conference on Natural Language Generation

• Publication date

  2000-06-12

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.3115/1118253.1118268
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Minimal Recursion Semantics: An Introduction

  2005cited by this paper
• Segregatory Coordination and Ellipsis in Text Generation

  1998cited by this paper
• An Architecture for Opportunistic Text Generation

  1998cited by this paper
• Introduction to Natural Language Semantics

  1998cited by this paper
• An Algorithm for Generating Referential Descriptions with Flexible Interfaces

  1997cited by this paper
• Type-Logical Semantics

  1997cited by this paper
• Language Generation for Multimedia Healthcare Briefings

  1997cited by this paper
• Defeasible Rules in Content Selection and Text Structuring

  1997cited by this paper
• An Algorithm for Generating Quantifiers

  1996cited by this paper
• MAGIC: an experimental system for generating multimedia briefings about post-bypass patient status.

  1996cited by this paper
• Computational Interpretations of the Gricean Maxims in the Generation of Referring Expressions

  1995cited by this paper
• Quantifier Scope and Constituency

  1995cited by this paper
• Generating Referring Expressions: Constructing Descriptions in a Domain of Objects and Processes

  1995cited by this paper
• Revision-based generation of natural language summaries providing historical background: corpus-based analysis, design, implementation and evaluation

  1995cited by this paper
• Research Paper: Knowledge-based Approaches to the Maintenance of a Large Controlled Medical Terminology

  1994cited by this paper
• A Fast Algorithm for the Generation of Referring Expressions

  1992cited by this paper
• Applied Text Generation

  1992cited by this paper
• Controlling Content Realization with Functional Unification Grammars

  1992cited by this paper
• Categorial Semantics and Scoping

  1990cited by this paper
• CLASSIC: a structural data model for objects

  1989cited by this paper
• Expressing quantifier scope in French generation

  1988cited by this paper
• An Algorithm for Generating Quantifier Scopings

  1987cited by this paper
• TEAM: An Experiment in the Design of Transportable Natural-Language Interfaces

  1987cited by this paper
• Semantics and Quantification in Natural Language Question Answering

  1986cited by this paper
• Everything That Linguists Have Always Wanted to Know About Logic But Were Ashamed to Ask

  1985cited by this paper
• Text generation: using discourse strategies and focus constraints to generate natural language text

  1985cited by this paper
• Determiners : A Relational Perspective

  1983cited by this paper
• Generalized quantifiers and natural language

  1981cited by this paper
• I.—EACH AND EVERY, ANY AND ALL

  1962cited by this paper
• A Functional Grammar

  1946cited by this paper

• What does the Failure to Reason with “Respectively” in Zero/Few-Shot Settings Tell Us about Language Models?

  2023cites this paper
• Fuzzy Quantified Relational Properties for Referring Expression Generation

  2022influential citation
• Quantification: The View From Natural Language Generation

  2021cites this paper
• Computational Models of Referring

  2019cites this paper
• A Translation from Logic to English with Dynamic Semantics

  2009cites this paper
• Text Generation in Clinical Medicine – a Review

  2003cites this paper
• Clause aggregation: an approach to generating concise text

  2002cites this paper