Beginning September, 2004, several researchers have been collaborating to produce detailed semantic annotation of two difficult sentences. The effort aims to produce a single unified representation that goes beyond what may currently be feasible to annotate consistantly or to generate automatically. Rather this ``pie in the sky'' annotation effort is an attempt at defining a future goal for semantic analysis.

@misc{meyers:2005, author = {Meyers, Adam}, title = {Pie in the Sky Description}, year = {2005}, note = {Last visited 1 April 2005}, url = {http://nlp.cs.nyu.edu/meyers/pie-in-the-sky.html}, keywords = {semantics annotation}, abstract = {Beginning September, 2004, several researchers have been collaborating to produce detailed semantic annotation of two difficult sentences. The effort aims to produce a single unified representation that goes beyond what may currently be feasible to annotate consistantly or to generate automatically. Rather this ``pie in the sky'' annotation effort is an attempt at defining a future goal for semantic analysis.} }

%0 = misc %A = Meyers, Adam %B = } %C = %D = 2005 %I = %T = Pie in the Sky Description} %U = http://nlp.cs.nyu.edu/meyers/pie-in-the-sky.html

Although with the Semantic Web initiative much research on web page semantic annotation has already been done by AI researchers, linguistic text annotation, including the semantic one, was originally developed in Corpus Linguistics and its results have been somehow neglected by AI. The purpose of the research presented in this proposal is to prove that integration of results in both fields is not only possible, but also highly useful in order to make Semantic Web pages more machine-readable...

@inproceedings{Aguado:2003, author = {Aguado de Cea, Guadalupe and Álvarez de Mon, Inmaculada and Gómez Pérez, Asunción and Pareja-Lora, Antonio and Plaza-Arteche, Rosario}, title = {A Semantic Web Page Linguistic Annotation Model}, booktitle = {Semantic Web Meets Language Resources -- Papers from the AAAI Workshop}, publisher = {AAAI Press}, year = {2003}, pages = {20-29}, note = {Technical Report WS-02-16}, url = {http://www.cs.vassar.edu/ide/events/ParejaLora.pdf}, keywords = {semantic_web annotation}, abstract = {Although with the Semantic Web initiative much research on web page semantic annotation has already been done by AI researchers, linguistic text annotation, including the semantic one, was originally developed in Corpus Linguistics and its results have been somehow neglected by AI. The purpose of the research presented in this proposal is to prove that integration of results in both fields is not only possible, but also highly useful in order to make Semantic Web pages more machine-readable...} }

%0 = inproceedings %A = Aguado de Cea, Guadalupe and Álvarez de Mon, Inmaculada and Gómez Pérez, Asunción and Pareja-Lora, Antonio and Plaza-Arteche, Rosario %B = Semantic Web Meets Language Resources -- Papers from the AAAI Workshop %D = 2003 %I = AAAI Press %T = A Semantic Web Page Linguistic Annotation Model %U = http://www.cs.vassar.edu/ide/events/ParejaLora.pdf

`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 focused 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.

@article{Bird:2001, author = {Bird, Steven and Liberman, Mark}, title = {A Formal Framework for Linguistic Annotation}, journal = {Speech Communication}, year = {2003}, volume = {33}, number = {1,2}, pages = {23-60}, url = {http://www.ldc.upenn.edu/sb/home/publications.html}, keywords = {annotation speech}, abstract = {`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 focused 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.} }

%0 = article %A = Bird, Steven and Liberman, Mark %D = 2003 %T = A Formal Framework for Linguistic Annotation %U = http://www.ldc.upenn.edu/sb/home/publications.html

As language data and associated technologies proliferate and as the language resources community expands, it is becoming increasingly difficult to locate and reuse existing resources. Are there any lexical resources for such-and-such a language? What tool works with transcripts in this particular format? What is a good format to use for linguistic data of this type? Questions like these dominate many mailing lists, since web search engines are an unreliable way to find language resources. This paper reports on a new digital infrastructure for discovering language resources being developed by the Open Language Archives Community (OLAC). At the core of OLAC is its metadata format, which is designed to facilitate description and discovery of all kinds of language resources, including data, tools, or advice. The paper describes OLAC metadata, its relationship to Dublin Core metadata, and its dissemination using the metadata harvesting protocol of the Open Archives Initiative.

@article{Bird:2003, author = {Bird, Steven and Simons, Gary}, title = {Extending Dublin Core Metadata to Support the Description and Discovery of Language Resources}, journal = {Computing and the Humanities}, year = {2003}, volume = {37}, number = {4}, url = {http://arxiv.org/abs/cs.CL/0308022}, keywords = {annotation}, abstract = {As language data and associated technologies proliferate and as the language resources community expands, it is becoming increasingly difficult to locate and reuse existing resources. Are there any lexical resources for such-and-such a language? What tool works with transcripts in this particular format? What is a good format to use for linguistic data of this type? Questions like these dominate many mailing lists, since web search engines are an unreliable way to find language resources. This paper reports on a new digital infrastructure for discovering language resources being developed by the Open Language Archives Community (OLAC). At the core of OLAC is its metadata format, which is designed to facilitate description and discovery of all kinds of language resources, including data, tools, or advice. The paper describes OLAC metadata, its relationship to Dublin Core metadata, and its dissemination using the metadata harvesting protocol of the Open Archives Initiative.} }

%0 = article %A = Bird, Steven and Simons, Gary %D = 2003 %T = Extending Dublin Core Metadata to Support the Description and Discovery of Language Resources %U = http://arxiv.org/abs/cs.CL/0308022

Recently, reading comprehension tests for students and adult language learners have received increased attention within the NLP community as a means to develop and evaluate robust question answering (NLQA) methods. We present our ongoing work on automatically creating richly annotated corpus resources for NLQA and on comparing automatic methods for answering questions against this data set. Starting with the CBC4Kids corpus, we have added XML annotation layers for tokenization, lemmatization, stemming, semantic classes, POS tags and best anking syntactic parses to support future experiments with semantic answer retrieval and inference. Using this resource, we have calculated a baseline for word-overlap based answer retrieval (Hirschman et al., 1999) on the CBC4Kids data and found the method performs slightly better than on the REMEDIA corpus. We hope that our richly annotated version of the CBC4Kids corpus will become a standard resource, especially as a controlled environment for evaluating inference-based techniques.

@inproceedings{Dalmas:2003, author = {Dalmas, Tiphaine and Leidner, Jochen L. and Webber, Bonnie and Grover, Claire and Bos, Johan}, title = {Generating Annotated Corpora for Reading Comprehension and Question Answering Evaluation.}, booktitle = {Proc. EACL 2003 workshop on NLP for Question Answering}, year = {2003}, pages = {13-19}, url = {http://www.iccs.informatics.ed.ac.uk/~s0239229/documents/publications.html}, keywords = {annotation question_answering}, abstract = {Recently, reading comprehension tests for students and adult language learners have received increased attention within the NLP community as a means to develop and evaluate robust question answering (NLQA) methods. We present our ongoing work on automatically creating richly annotated corpus resources for NLQA and on comparing automatic methods for answering questions against this data set. Starting with the CBC4Kids corpus, we have added XML annotation layers for tokenization, lemmatization, stemming, semantic classes, POS tags and best anking syntactic parses to support future experiments with semantic answer retrieval and inference. Using this resource, we have calculated a baseline for word-overlap based answer retrieval (Hirschman et al., 1999) on the CBC4Kids data and found the method performs slightly better than on the REMEDIA corpus. We hope that our richly annotated version of the CBC4Kids corpus will become a standard resource, especially as a controlled environment for evaluating inference-based techniques.} }

%0 = inproceedings %A = Dalmas, Tiphaine and Leidner, Jochen L. and Webber, Bonnie and Grover, Claire and Bos, Johan %B = Proc. EACL 2003 workshop on NLP for Question Answering %D = 2003 %T = Generating Annotated Corpora for Reading Comprehension and Question Answering Evaluation. %U = http://www.iccs.informatics.ed.ac.uk/~s0239229/documents/publications.html

MPEG-7 (Moving Picture Experts Group Phase 7) is an XML-based international standard on semantic description of multimedia content. This document discusses the Linguistic DS and related tools. The linguistic DS is a tool, based on the GDA tag set (http://i-content.org/GDA/tagset.html), for semantic annotation of linguistic data in or associated with multimedia content. The current document text reflects `Study of FPDAM - MPEG-7 MDS Extensions' issued in March 2003, and not most part of MPEG-7 MDS, for which the readers are referred to the first version of MPEG-7 MDS document available from ISO (http://www.iso.org). Without that reference, however, this document should be mostly intelligible to those who are familiar with XML and linguistic theories. Comments are welcome and will be considered in the standardization process.

@techreport{Hasida:2003, author = {Hasida, Kôiti}, title = {The Linguistic DS: Linguistic Description in MPEG-7}, year = {2003}, url = {http://arxiv.org/abs/cs.CL/0307044}, keywords = {annotation}, abstract = {MPEG-7 (Moving Picture Experts Group Phase 7) is an XML-based international standard on semantic description of multimedia content. This document discusses the Linguistic DS and related tools. The linguistic DS is a tool, based on the GDA tag set (http://i-content.org/GDA/tagset.html), for semantic annotation of linguistic data in or associated with multimedia content. The current document text reflects `Study of FPDAM - MPEG-7 MDS Extensions' issued in March 2003, and not most part of MPEG-7 MDS, for which the readers are referred to the first version of MPEG-7 MDS document available from ISO (http://www.iso.org). Without that reference, however, this document should be mostly intelligible to those who are familiar with XML and linguistic theories. Comments are welcome and will be considered in the standardization process.} }

%0 = techreport %A = Hasida, Kôiti %B = } %C = %D = 2003 %I = %T = The Linguistic DS: Linguistic Description in MPEG-7} %U = http://arxiv.org/abs/cs.CL/0307044

Because the ultimate purpose of the Semantic Web is to help users locate, organize, and process information, we strongly believe that it should be grounded in the information access method humans are most comfortable with --natural language. However, the Resource Description Framework (RDF), the foundation of the Semantic Web, was designed to be easily processed by computers, not humans. To render RDF friendlier to humans, we propose to augment it with natural language annotations, or metadata written in everyday language. We argue that natural language annotations are not only intuitive and e.ective, but can also accelerate the pace with which the Semantic Web is being adopted. We demonstrate the use of natural language annotations from within Haystack, an end user Semantic Web platform that also serves as a testbed for our ideas. In addition to a prototype SemanticWeb question answering system, we describe other opportunities for marrying natural language and Semantic Web technology.

@inproceedings{Katz:2002d, author = {Katz, Boris and Lin, Jimmy and Quan, Dennis}, title = {Natural Language Annotations for the Semantic Web}, booktitle = {Proc. ODBASE 2002}, year = {2002}, url = {http://www.ai.mit.edu/people/jimmylin/publications/}, keywords = {question_answering semantic_web annotation}, abstract = {Because the ultimate purpose of the Semantic Web is to help users locate, organize, and process information, we strongly believe that it should be grounded in the information access method humans are most comfortable with ---natural language. However, the Resource Description Framework (RDF), the foundation of the Semantic Web, was designed to be easily processed by computers, not humans. To render RDF friendlier to humans, we propose to augment it with natural language annotations, or metadata written in everyday language. We argue that natural language annotations are not only intuitive and e.ective, but can also accelerate the pace with which the Semantic Web is being adopted. We demonstrate the use of natural language annotations from within Haystack, an end user Semantic Web platform that also serves as a testbed for our ideas. In addition to a prototype SemanticWeb question answering system, we describe other opportunities for marrying natural language and Semantic Web technology.} }

%0 = inproceedings %A = Katz, Boris and Lin, Jimmy and Quan, Dennis %B = Proc. ODBASE 2002 %D = 2002 %T = Natural Language Annotations for the Semantic Web %U = http://www.ai.mit.edu/people/jimmylin/publications/

@techreport{Day:2000, author = {Day, Neil and Martinez, José M.}, title = {Introduction to MPEG-7}, year = {2000}, number = {ISO/IECT JTC1/SC29/WG11 N3751}, keywords = {annotation} }

%0 = techreport %A = Day, Neil and Martinez, José M. %B = } %C = %D = 2000 %I = %T = Introduction to MPEG-7} %U =

This paper describes a method for annotating coreference on long, narrative texts and its associated tools. Several mark up possibilities are discussed, including the MUC-6 and 7 conventions. The developed tools are integrated into a reference resolution workbench. The resources built with these tools can help tuning parameters of our reference solver, using a simple but effective gradient ascent method.

@inproceedings{Popescu:1998, author = {Popescu-Belis, Andrei}, title = {How Corpora with Annotated Coreference Links Improve Reference Resolution}, booktitle = {Proc. LREC'98}, address = {Granada, Spain}, year = {1998}, pages = {567-572}, url = {http://andreipb.free.fr/publications.html}, keywords = {anaphora annotation}, abstract = {This paper describes a method for annotating coreference on long, narrative texts and its associated tools. Several mark up possibilities are discussed, including the MUC-6 and 7 conventions. The developed tools are integrated into a reference resolution workbench. The resources built with these tools can help tuning parameters of our reference solver, using a simple but effective gradient ascent method.} }

%0 = inproceedings %A = Popescu-Belis, Andrei %B = Proc. LREC'98 %C = Granada, Spain %D = 1998 %T = How Corpora with Annotated Coreference Links Improve Reference Resolution %U = http://andreipb.free.fr/publications.html