This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

https://www.foo.be/cours/dess-20122013/b/Natural%20Language%20Processing%20with%20Python%20-%20O'Reilly2009.pdf

Natural Language Processing with Python

語用論(Pragmatics)を考える

This paper introduces the Multi-Genre Natural Language Inference (MultiNLI) corpus, a dataset designed for use in the development and evaluation of machine learning models for sentence understanding. At 433k examples, this resource is one of the largest corpora available for natural language inference (a.k.a. recognizing textual entailment), improving upon available resources in both its coverage and difficulty. MultiNLI accomplishes this by offering data from ten distinct genres of written and spoken English, making it possible to evaluate systems on nearly the full complexity of the language, while supplying an explicit setting for evaluating cross-genre domain adaptation. In addition, an evaluation using existing machine learning models designed for the Stanford NLI corpus shows that it represents a substantially more difficult task than does that corpus, despite the two showing similar levels of inter-annotator agreement.

A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

The semantics of definite and indefinite noun phrases : a dissertation

According to the alternative semantics for focus, the semantic reflec of intonational focus is a second semantic value, which in the case of a sentence is a set of propositions. We examine a range of semantic and pragmatic applications of the theory, and extract a unitary principle specifying how the focus semantic value interacts with semantic and pragmatic processes. A strong version of the theory has the effect of making lexical or construction-specific stipulation of a focus-related effect in association-with-focus constructions impossible. Furthermore, while focus has a uniform import, the sources of meaning differences in association with focus are various.

https://www.sfs.uni-tuebingen.de/~astechow/Lehre/SS06/Focus/rooth92.pdf

A theory of focus interpretation

Preface. 1. Truth-conditional Semantics and the Fregean Program. 2. Executing the Fregean Program. 3. Semantics and Syntax. 4. More of English: Non-verbal Predicates, Modifiers, Definite Descriptions. 5. Relative Clauses, Variables, Variable Binding. 6. Quantifiers: Their Semantic Type. 7. Quantification and Grammar. 8. Syntactic and Semantic Constraints on Quantifier Movement. 9. Bound and Referential Pronouns and Ellipsis. 10. Syntactic and Semantic Binding. 11. E-Type Anaphora. 12. First Steps Towards an Intensional Semantics. Index.

Semantics in generative grammar

In his analysis of action sentences, Donald Davidson drew a clear distinction between arguments and adjuncts. Neglecting temporal relations, sentences like 

(1)

We bought your slippers in Marrakesh.

Severing the External Argument from its Verb

/pdf/the-notional-category-of-modality-19ajwln9fb.pdf

The Notional Category of Modality

/pdf/stage-level-and-individual-level-predicates-12q7laqo9v.pdf

Stage-Level and Individual-Level Predicates

In this paper I offer an account of the meaning of ‘must’ and ‘can’ within the framework of possible worlds semantics. The paper consists of two parts: the first argues for a relative concept of modality underlying modal words like ‘must’ and ‘can’ in natural language. I give preliminary definitions of the meaning of these words which are formulated in terms of logical consequence and compatibility, respectively. The second part discusses one kind of insufficiency in the meaning definitions given in the first part, which arise from the ‘ex falso quodlibet’ paradox of logical consequence. In stepwise fashion, I make an attempt to avoid most of the consequences of this paradox for the meaning definitions of ‘must’ and ‘can’.

Angelika Kratzer

Papers

Semantics in generative grammar

Severing the External Argument from its Verb

The Notional Category of Modality

Stage-Level and Individual-Level Predicates

What ‘must’ and ‘can’ must and can mean