11,674 research outputs found
A Formal Framework for Linguistic Annotation
`Linguistic annotation' covers any descriptive or analytic notations applied
to raw language data. The basic data may be in the form of time functions --
audio, video and/or physiological recordings -- or it may be textual. The added
notations may include transcriptions of all sorts (from phonetic features to
discourse structures), part-of-speech and sense tagging, syntactic analysis,
`named entity' identification, co-reference annotation, and so on. While there
are several ongoing efforts to provide formats and tools for such annotations
and to publish annotated linguistic databases, the lack of widely accepted
standards is becoming a critical problem. Proposed standards, to the extent
they exist, have focussed on file formats. This paper focuses instead on the
logical structure of linguistic annotations. We survey a wide variety of
existing annotation formats and demonstrate a common conceptual core, the
annotation graph. This provides a formal framework for constructing,
maintaining and searching linguistic annotations, while remaining consistent
with many alternative data structures and file formats.Comment: 49 page
ATLAS: A flexible and extensible architecture for linguistic annotation
We describe a formal model for annotating linguistic artifacts, from which we
derive an application programming interface (API) to a suite of tools for
manipulating these annotations. The abstract logical model provides for a range
of storage formats and promotes the reuse of tools that interact through this
API. We focus first on ``Annotation Graphs,'' a graph model for annotations on
linear signals (such as text and speech) indexed by intervals, for which
efficient database storage and querying techniques are applicable. We note how
a wide range of existing annotated corpora can be mapped to this annotation
graph model. This model is then generalized to encompass a wider variety of
linguistic ``signals,'' including both naturally occuring phenomena (as
recorded in images, video, multi-modal interactions, etc.), as well as the
derived resources that are increasingly important to the engineering of natural
language processing systems (such as word lists, dictionaries, aligned
bilingual corpora, etc.). We conclude with a review of the current efforts
towards implementing key pieces of this architecture.Comment: 8 pages, 9 figure
Annotation Graphs and Servers and Multi-Modal Resources: Infrastructure for Interdisciplinary Education, Research and Development
Annotation graphs and annotation servers offer infrastructure to support the
analysis of human language resources in the form of time-series data such as
text, audio and video. This paper outlines areas of common need among empirical
linguists and computational linguists. After reviewing examples of data and
tools used or under development for each of several areas, it proposes a common
framework for future tool development, data annotation and resource sharing
based upon annotation graphs and servers.Comment: 8 pages, 6 figure
Experiences with the GTU grammar development environment
In this paper we describe our experiences with a tool for the development and
testing of natural language grammars called GTU (German:
Grammatik-Testumgebumg; grammar test environment). GTU supports four grammar
formalisms under a window-oriented user interface. Additionally, it contains a
set of German test sentences covering various syntactic phenomena as well as
three types of German lexicons that can be attached to a grammar via an
integrated lexicon interface. What follows is a description of the experiences
we gained when we used GTU as a tutoring tool for students and as an
experimental tool for CL researchers. From these we will derive the features
necessary for a future grammar workbench.Comment: 7 pages, uses aclap.st
Software Infrastructure for Natural Language Processing
We classify and review current approaches to software infrastructure for
research, development and delivery of NLP systems. The task is motivated by a
discussion of current trends in the field of NLP and Language Engineering. We
describe a system called GATE (a General Architecture for Text Engineering)
that provides a software infrastructure on top of which heterogeneous NLP
processing modules may be evaluated and refined individually, or may be
combined into larger application systems. GATE aims to support both researchers
and developers working on component technologies (e.g. parsing, tagging,
morphological analysis) and those working on developing end-user applications
(e.g. information extraction, text summarisation, document generation, machine
translation, and second language learning). GATE promotes reuse of component
technology, permits specialisation and collaboration in large-scale projects,
and allows for the comparison and evaluation of alternative technologies. The
first release of GATE is now available - see
http://www.dcs.shef.ac.uk/research/groups/nlp/gate/Comment: LaTeX, uses aclap.sty, 8 page
GATE -- an Environment to Support Research and Development in Natural Language Engineering
We describe a software environment to support research and development in natural language (NL) engineering. This environment -- GATE (General Architecture for Text Engineering) -- aims to advance research in the area of machine processing of natural languages by providing a software infrastructure on top of which heterogeneous NL component modules may be evaluated and refined individually or may be combined into larger application systems. Thus, GATE aims to support both researchers and developers working on component technologies (e.g. parsing, tagging, morphological analysis) and those working on developing end-user applications (e.g. information extraction, text summarisation, document generation, machine translation, and second language learning). GATE will promote reuse of component technology, permit specialisation and collaboration in large-scale projects, and allow for the comparison and evaluation of alternative technologies. The first release of GATE is now available
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A multimodal restaurant finder for semantic web
Multimodal dialogue systems provide multiple modalities in the form of speech, mouse clicking, drawing or touch that can enhance human-computer interaction. However, one of the drawbacks of the existing multimodal systems is that they are highly domain-specific and they do not allow information to be shared across different providers. In this paper, we propose a semantic multimodal system, called Semantic Restaurant Finder, for the Semantic Web in which the restaurant information in different city/country/language are constructed as ontologies to allow the information to be sharable. From the Semantic Restaurant Finder, users can make use of the semantic restaurant knowledge distributed from different locations on the Internet to find the desired restaurants
A framework for lexical representation
In this paper we present a unification-based lexical platform designed for
highly inflected languages (like Roman ones). A formalism is proposed for
encoding a lemma-based lexical source, well suited for linguistic
generalizations. From this source, we automatically generate an allomorph
indexed dictionary, adequate for efficient processing. A set of software tools
have been implemented around this formalism: access libraries, morphological
processors, etc.Comment: 9 page
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