James Pustejovsky – författare

This reader collects and introduces important work in linguistics, computer science, artificial intelligence, and computational linguistics on the use of linguistic devices in natural languages to situate events in time: whether they are past, present, or future; whether they are real or hypothetical; when an event might have occurred, and how long it could have lasted. In focussing on the treatment and retrieval of time-based information it seeks to lay the foundation for temporally-aware natural language computer processing systems, for example those that process documents on the worldwide web to answer questions or produce summaries. The development of such systems requires the application of technical knowledge from many different disciplines. The book is the first to bring these disciplines together, by means of classic and contemporary papers in four areas: tense, aspect, and event structure; temporal reasoning; the temporal structure of natural language discourse; and temporal annotation. Clear, self-contained editorial introductions to each area provide the necessary technical background for the non-specialist, explaining the underlying connections across disciplines.A wide range of students and professionals in academia and industry will value this book as an introduction and guide to a new and vital technology. The former include researchers, students, and teachers of natural language processing, linguistics, artificial intelligence, computational linguistics, computer science, information retrieval (including the growing speciality of question-answering), library sciences, human-computer interaction, and cognitive science. Those in industry include corporate managers and researchers, software product developers, and engineers in information-intensive companies, such as on-line database and web-service providers.

Interpreting Motion presents an integrated perspective on how language structures constrain concepts of motion and how the world shapes the way motion is linguistically expressed. Natural language allows for efficient communication of elaborate descriptions of movement without requiring a precise specification of the motion. Interpreting Motion is the first book to analyze the semantics of motion expressions in terms of the formalisms of qualitative spatialreasoning. It shows how motion descriptions in language are mapped to trajectories of moving entities based on qualitative spatio-temporal relationships. The authors provide an extensive discussion of prior research on spatial prepositions and motion verbs, devoting chapters to the compositional semantics ofmotion sentences, the formal representations needed for computers to reason qualitatively about time, space, and motion, and the methodology for annotating corpora with linguistic information in order to train computer programs to reproduce the annotation. The applications they illustrate include route navigation, the mapping of travel narratives, question-answering, image and video tagging, and graphical rendering of scenes from textual descriptions.The book is written accessibly for a broad scientific audience of linguists, cognitive scientists, computer scientists, and those working in fields such as artificial intelligence and geographic information systems.

Lexical ambiguity is one of the most intractable problems facing language processing studies and, not surprisingly, it is at the core of research in lexical semantics. The papers in this collection constitute not just a set of diverse yet related articles in this core area of research, but rather make up a unique collection of work on the relationship between logical polysemy, sense extension, and discourse structure. Each paper addresses the following questions: what is the representation of a lexical item such that it may assume different senses? What is it about the representation of a lexical item that gives rise to sense extensions and to the phenomenon of logical polysemy? Three major subthemes run through the papers: the role of pragmatics and discourse in lexical disambiguation; the analysis of logical polysemy as a compositional process; and the treament of sense extension and referential transfer phenomena.

This book investigates the nature of generalization in language and examines how language is known by adults and acquired by children. It looks at how and why constructions are learned, the relation between their forms and functions, and how cross-linguistic and language-internal generalizations about them can be explained. Constructions at Work is divided into three parts: in the first Professor Goldberg provides an overview of constructionist approaches, including the constructionist approach to argument structure, and argues for a usage-based model of grammar. In Part II she addresses issues concerning how generalizations are constrained and constructional generalizations are learned. In Part III the author shows that a combination of function and processing accounts for a wide range of language-internal and cross-linguistic generalizations. She then considers the degree to which the function of constructions explains their distribution and examines cross-linguistic tendencies in argument realization. She demonstrates that pragmatic and cognitive processes account for the data without appeal to stipulations that are language-specific.This book is an important contribution to the study of how language operates in the mind and in the world and how these operations relate. It is of central interest for scholars and graduate-level students in all branches of theoretical linguistics and psycholinguistics. It will also appeal to cognitive scientists and philosophers concerned with language and its acquisition.

This reader collects and introduces important work in linguistics, computer science, artificial intelligence, and computational linguistics on the use of linguistic devices in natural languages to situate events in time: whether they are past, present, or future; whether they are real or hypothetical; when an event might have occurred, and how long it could have lasted. Clear, self-contained editorial introductions to each area provide the necessary technical background for the non-specialist, explaining the underlying connections across disciplines.

Interpreting Motion presents an integrated perspective on how language structures constrain concepts of motion and how the world shapes the way motion is linguistically expressed. Natural language allows for efficient communication of elaborate descriptions of movement without requiring a precise specification of the motion. Interpreting Motion is the first book to analyze the semantics of motion expressions in terms of the formalisms of qualitative spatial reasoning. It shows how motion descriptions in language are mapped to trajectories of moving entities based on qualitative spatio-temporal relationships. The authors provide an extensive discussion of prior research on spatial prepositions and motion verbs, devoting chapters to the compositional semantics of motion sentences, the formal representations needed for computers to reason qualitatively about time, space, and motion, and the methodology for annotating corpora with linguistic information in order to train computer programs to reproduce the annotation. The applications they illustrate include route navigation, the mapping of travel narratives, question-answering, image and video tagging, and graphical rendering of scenes from textual descriptions.The book is written accessibly for a broad scientific audience of linguists, cognitive scientists, computer scientists, and those working in fields such as artificial intelligence and geographic information systems.

What is the lexicon, what does it contain, and how is it structured? What principles determine the functioning of the lexicon as a component of natural language grammar? What role does lexical information play in linguistic theory? This accessible introduction aims to answer these questions, and explores the relation of the lexicon to grammar as a whole. It includes a critical overview of major theoretical frameworks, and puts forward a unified treatment of lexical structure and design. The text can be used for introductory and advanced courses, and for courses that touch upon different aspects of the lexicon, such as lexical semantics, lexicography, syntax, general linguistics, computational lexicology and ontology design. The book provides students with a set of tools which will enable them to work with lexical data for all kinds of purposes, including an abundance of exercises and in-class activities designed to ensure that students are actively engaged with the content and effectively acquire the necessary knowledge and skills they need.

What is the lexicon, what does it contain, and how is it structured? What principles determine the functioning of the lexicon as a component of natural language grammar? What role does lexical information play in linguistic theory? This accessible introduction aims to answer these questions, and explores the relation of the lexicon to grammar as a whole. It includes a critical overview of major theoretical frameworks, and puts forward a unified treatment of lexical structure and design. The text can be used for introductory and advanced courses, and for courses that touch upon different aspects of the lexicon, such as lexical semantics, lexicography, syntax, general linguistics, computational lexicology and ontology design. The book provides students with a set of tools which will enable them to work with lexical data for all kinds of purposes, including an abundance of exercises and in-class activities designed to ensure that students are actively engaged with the content and effectively acquire the necessary knowledge and skills they need.

This book integrates the research being carried out in the field of lexical semantics in linguistics with the work on knowledge representation and lexicon design in computational linguistics. Rarely do these two camps meet and discuss the demands and concerns of each other's fields. Therefore, the book is interesting in that it provides a stimulating and unique discussion between the computational perspective of lexical meaning and the concerns of the linguist for the semantic description of lexical items in the context of syntactic descriptions. The volume is divided into three sections. Part one deals with the fundamentals of lexical structure and what constitutes a lexical semantic representation for a grammatical theory. Part two deals with the specific mappings that are necessary from a lexical semantic representation to the syntax. Finally, Part three addresses the possibility of modeling lexical knowledge with computational uses in mind. The unifying assumption behind all these works is that methodologies in computational linguistics and theoretical linguistics have converged, and that the goals of both fields are the same: to investigate the phenomenon of language in a rigorous and analytic way, for the purpose of establishing how it fits into the larger domain of intelligent human behavior.

The goal of this book is to integrate the research being carried out in the field of lexical semantics in linguistics with the work on knowledge representation and lexicon design in computational linguistics. Rarely do these two camps meet and discuss the demands and concerns of each other's fields. Therefore, this book is interesting in that it provides a stimulating and unique discussion between the computational perspective of lexical meaning and the concerns of the linguist for the semantic description of lexical items in the context of syntactic descriptions. This book grew out of the papers presented at a workshop held at Brandeis University in April, 1988, funded by the American Association for Artificial Intelligence. The entire workshop as well as the discussion periods accom­ panying each talk were recorded. Once complete copies of each paper were available, they were distributed to participants, who were asked to provide written comments on the texts for review purposes. VII JAMES PUSTEJOVSKY 1. INTRODUCTION There is currently a growing interest in the content of lexical entries from a theoretical perspective as well as a growing need to understand the organization of the lexicon from a computational view. This volume attempts to define the directions that need to be taken in order to achieve the goal of a coherent theory of lexical organization.

What is the lexicon, what does it contain, and how is it structured? What principles determine the functioning of the lexicon as a component of natural language grammar? What role does lexical information play in linguistic theory? This accessible introduction aims to answer these questions, and explores the relation of the lexicon to grammar as a whole. It includes a critical overview of major theoretical frameworks, and puts forward a unified treatment of lexical structure and design. The text can be used for introductory and advanced courses, and for courses that touch upon different aspects of the lexicon, such as lexical semantics, lexicography, syntax, general linguistics, computational lexicology and ontology design. The book provides students with a set of tools which will enable them to work with lexical data for all kinds of purposes, including an abundance of exercises and in-class activities designed to ensure that students are actively engaged with the content and effectively acquire the necessary knowledge and skills they need.

Create your own natural language training corpus for machine learning. This example-driven book walks you through the annotation cycle, from selecting an annotation task and creating the annotation specification to designing the guidelines, creating a "gold standard" corpus, and then beginning the actual data creation with the annotation process. Systems exist for analyzing existing corpora, but making a new corpus can be extremely complex. To help you build a foundation for your own machine learning goals, this easy-to-use guide includes case studies that demonstrate four different annotation tasks in detail. You'll also learn how to use a lightweight software package for annotating texts and adjudicating the annotations. This book is a perfect companion to O'Reilly's Natural Language Processing with Python, which describes how to use existing corpora with the Natural Language Toolkit.

Create your own natural language training corpus for machine learning. Whether you’re working with English, Chinese, or any other natural language, this hands-on book guides you through a proven annotation development cycle—the process of adding metadata to your training corpus to help ML algorithms work more efficiently. You don’t need any programming or linguistics experience to get started.

Using detailed examples at every step, you’ll learn how the MATTER Annotation Development Process helps you Model, Annotate, Train, Test, Evaluate, and Revise your training corpus. You also get a complete walkthrough of a real-world annotation project.

Define a clear annotation goal before collecting your dataset (corpus)Learn tools for analyzing the linguistic content of your corpusBuild a model and specification for your annotation projectExamine the different annotation formats, from basic XML to the Linguistic Annotation FrameworkCreate a gold standard corpus that can be used to train and test ML algorithmsSelect the ML algorithms that will process your annotated dataEvaluate the test results and revise your annotation taskLearn how to use lightweight software for annotating texts and adjudicating the annotations

This book is a perfect companion to O’Reilly’s Natural Language Processing with Python.

This book provides an overview of multiple aspects of spatial language understanding and explores recent trends of modeling based on very large foundational models and their applications.  The authors address the following five main themes: spatial semantic representations in both symbolic and sub-symbolic spaces; spatial information extraction computational models; reasoning over spatial language; commonsense spatial understanding; and multiple modern and state-of-the-art downstream applications of spatial language understanding including dialogue systems, narrative discourse, and grounding language in the physical world with the multi-modal problem settings.  One of the essential functions of natural language is to express spatial relationships between objects.  Linguistic constructs can encode highly complex structures of objects, spatial relations between them, and patterns of motion through space relative to a reference point.  The complexity of spatial language understanding and its importance in downstream tasks that involve grounding the language in the physical world has become evident and important to the natural language processing research community.  In addition, this topic has recently attracted the attention of various sub-communities in the intersection of natural language, computer vision, and robotics.

This book provides an overview of multiple aspects of spatial language understanding and explores recent trends of modeling based on very large foundational models and their applications.  The authors address the following five main themes: spatial semantic representations in both symbolic and sub-symbolic spaces; spatial information extraction computational models; reasoning over spatial language; commonsense spatial understanding; and multiple modern and state-of-the-art downstream applications of spatial language understanding including dialogue systems, narrative discourse, and grounding language in the physical world with the multi-modal problem settings.  One of the essential functions of natural language is to express spatial relationships between objects.  Linguistic constructs can encode highly complex structures of objects, spatial relations between them, and patterns of motion through space relative to a reference point.  The complexity of spatial language understanding and its importance in downstream tasks that involve grounding the language in the physical world has become evident and important to the natural language processing research community.  In addition, this topic has recently attracted the attention of various sub-communities in the intersection of natural language, computer vision, and robotics.

Recent work on formal methods in computational lexicalsemantics has had theeffect of bringing many linguisticformalisms much closer to the knowledge representationlanguages used in artificial intelligence. Formalisms arenow emerging which may be more expressive and formallybetter understood than many knowledge representationlanguages. The interests of computational linguists nowextend to include such domains as commonsense knowledge,inheritance, default reasoning, collocational relations, andeven domain knowledge. With such an extension of the normalpurview of "linguistic" knowledge, one may question whetherthere is any logical justification for distinguishingbetween lexical semantics and commonsense reasoning.This volume explores the question from severalmethodologicaland theoretical perspectives. What emerges isa clear consensus that the notion of the lexicon and lexicalknowledge assumed in earlier linguistic research is grosslyinadequate and fails to address the deeper semantic issuesrequired for natural language analysis.

The Dagstuhl Seminar 05151 “Annotating, Extracting and Reasoning about Time and Events” took place April 10–15, 2005 at the International Conference and Research Center (IBFI), Schloss Dagstuhl, Germany. During the seminar, 17 leading researchers from 5 di?erent countries presented current research and discussed open problems concerning annotation, temporal reasoning, and event identi?cation. The work presented at this seminar, together with other previous andongoingresearch,centersaroundanemergingde factostandardfortime and event annotation: TimeML. TimeML has recently been adopted as a candidate for an ISO standard, and is currently being reviewed in this capacity. At the seminar, the discussions focussed on the following three Time- related issues: using the TimeML language e?ectively for consistent annotation, determining how useful such annotation is for further processing,and describing modi?cations that should be applied to the standard for applications such as question-answering and information retrieval. Discussions at the Dagstuhl Seminar led to new researchideas, and a variety ofpublicationsandconferenceandworkshoppresentationsresulted.Thiscurrent collection of papers adds to the growing body of work on TimeML. It focusses on important sub-areas within TimeML research such as temporal annotation and temporal reasoning and points to future research directions that are crucial for further progress.

The Dagstuhl Seminar 05151 “Annotating, Extracting and Reasoning about Time and Events” took place April 10–15, 2005 at the International Conference and Research Center (IBFI), Schloss Dagstuhl, Germany. During the seminar, 17 leading researchers from 5 di?erent countries presented current research and discussed open problems concerning annotation, temporal reasoning, and event identi?cation. The work presented at this seminar, together with other previous andongoingresearch,centersaroundanemergingde factostandardfortime and event annotation: TimeML. TimeML has recently been adopted as a candidate for an ISO standard, and is currently being reviewed in this capacity. At the seminar, the discussions focussed on the following three Time- related issues: using the TimeML language e?ectively for consistent annotation, determining how useful such annotation is for further processing,and describing modi?cations that should be applied to the standard for applications such as question-answering and information retrieval. Discussions at the Dagstuhl Seminar led to new researchideas, and a variety ofpublicationsandconferenceandworkshoppresentationsresulted.Thiscurrent collection of papers adds to the growing body of work on TimeML. It focusses on important sub-areas within TimeML research such as temporal annotation and temporal reasoning and points to future research directions that are crucial for further progress.

This book integrates the research being carried out in the field of lexical semantics in linguistics with the work on knowledge representation and lexicon design in computational linguistics. Rarely do these two camps meet and discuss the demands and concerns of each other's fields. Therefore, the book is interesting in that it provides a stimulating and unique discussion between the computational perspective of lexical meaning and the concerns of the linguist for the semantic description of lexical items in the context of syntactic descriptions. The volume is divided into three sections. Part one deals with the fundamentals of lexical structure and what constitutes a lexical semantic representation for a grammatical theory. Part two deals with the specific mappings that are necessary from a lexical semantic representation to the syntax. Finally, Part three addresses the possibility of modeling lexical knowledge with computational uses in mind. The unifying assumption behind all these works is that methodologies in computational linguistics and theoretical linguistics have converged, and that the goals of both fields are the same: to investigate the phenomenon of language in a rigorous and analytic way, for the purpose of establishing how it fits into the larger domain of intelligent human behavior.

This collection of papers takes linguists to the leading edge of techniques in generative lexicon theory, the linguistic composition methodology that arose from the imperative to provide a compositional semantics for the contextual modifications in meaning that emerge in real linguistic usage. Today’s growing shift towards distributed compositional analyses evinces the applicability of GL theory, and the contributions to this volume, presented at three international workshops (GL-2003, GL-2005 and GL-2007) address the relationship between compositionality in language and the mechanisms of selection in grammar that are necessary to maintain this property. The core unresolved issues in compositionality, relating to the interpretation of context and the mechanisms of selection, are treated from varying perspectives within GL theory, including its basic theoretical mechanisms and its analytical viewpoint on linguistic phenomena.

This collection of papers takes linguists to the leading edge of techniques in generative lexicon theory, the linguistic composition methodology that arose from the imperative to provide a compositional semantics for the contextual modifications in meaning that emerge in real linguistic usage. Today’s growing shift towards distributed compositional analyses evinces the applicability of GL theory, and the contributions to this volume, presented at three international workshops (GL-2003, GL-2005 and GL-2007) address the relationship between compositionality in language and the mechanisms of selection in grammar that are necessary to maintain this property. The core unresolved issues in compositionality, relating to the interpretation of context and the mechanisms of selection, are treated from varying perspectives within GL theory, including its basic theoretical mechanisms and its analytical viewpoint on linguistic phenomena.

The goal of this book is to integrate the research being carried out in the field of lexical semantics in linguistics with the work on knowledge representation and lexicon design in computational linguistics. Rarely do these two camps meet and discuss the demands and concerns of each other''s fields. Therefore, this book is interesting in that it provides a stimulating and unique discussion between the computational perspective of lexical meaning and the concerns of the linguist for the semantic description of lexical items in the context of syntactic descriptions. This book grew out of the papers presented at a workshop held at Brandeis University in April, 1988, funded by the American Association for Artificial Intelligence. The entire workshop as well as the discussion periods accom­ panying each talk were recorded. Once complete copies of each paper were available, they were distributed to participants, who were asked to provide written comments on the texts for review purposes. VII JAMES PUSTEJOVSKY 1. INTRODUCTION There is currently a growing interest in the content of lexical entries from a theoretical perspective as well as a growing need to understand the organization of the lexicon from a computational view. This volume attempts to define the directions that need to be taken in order to achieve the goal of a coherent theory of lexical organization.

This handbook offers a thorough treatment of the science of linguistic annotation. Leaders in the field guide the reader through the process of modeling, creating an annotation language, building a corpus and evaluating it for correctness. Essential reading for both computer scientists and linguistic researchers.Linguistic annotation is an increasingly important activity in the field of computational linguistics because of its critical role in the development of language models for natural language processing applications. Part one of this book covers all phases of the linguistic annotation process, from annotation scheme design and choice of representation format through both the manual and automatic annotation process, evaluation, and iterative improvement of annotation accuracy.  The second part of the book includes case studies of annotation projects across the spectrum of linguistic annotation types, including morpho-syntactic tagging, syntactic analyses, a range of semantic analyses (semantic roles, named entities, sentiment and opinion), time and event and spatial analyses, and discourse level analyses including discourse structure, co-reference, etc. Each case study addresses the various phases and processes discussed in the chapters of part one.

This handbook offers a thorough treatment of the science of linguistic annotation. Leaders in the field guide the reader through the process of modeling, creating an annotation language, building a corpus and evaluating it for correctness. Essential reading for both computer scientists and linguistic researchers.Linguistic annotation is an increasingly important activity in the field of computational linguistics because of its critical role in the development of language models for natural language processing applications. Part one of this book covers all phases of the linguistic annotation process, from annotation scheme design and choice of representation format through both the manual and automatic annotation process, evaluation, and iterative improvement of annotation accuracy.  The second part of the book includes case studies of annotation projects across the spectrum of linguistic annotation types, including morpho-syntactic tagging, syntactic analyses, a range of semantic analyses (semantic roles, named entities, sentiment and opinion), time and event and spatial analyses, and discourse level analyses including discourse structure, co-reference, etc. Each case study addresses the various phases and processes discussed in the chapters of part one.