The LDC Institute is a seminar series on issues in language data and database creation. The goals of the seminar series are to create a forum of UPenn affiliates with an interest in language data, to communicate LDC and UPenn experience in data collections, standards, and annotation, and to work with researchers and others who may be interested in LDC data or who may wish to contribute new data to the archives.

The topics covered will be descriptions of data-driven projects, both at the LDC and elsewhere and tutorials on specific methodologies and systems for dealing with language data. We assume attendees would be UPenn students, both undergraduate and graduate, as well as LDC staff who are interested.

Title and Instructor

In his presentation, Dr. Kendall describes his work on the Sociolinguistic Archive and Analysis Project (SLAAP), a web-based data preservation and exploration initiative centered at North Carolina State University. SLAAP houses audio recordings and associated materials from over 2,500 sociolinguistic interviews. In addition to its basic, preservational, organizational and access related features, a centerpiece of the archive is a time-aligned, databased transcription model which allows for dynamic, corpus-like analysis of the transcript data as well as real-time phonetic processing of the audio from the transcripts. The presentation describes the background of the project and its architecture, provides a demonstration of several of the web-based features, and discusses some of the ways that the archive and tools are being used in current sociolinguistic research.

Title and Instructor

This talk will report ongoing work on developing a corpus that includes all of the world's languages, represented in a consistent structure that permits large-scale cross-linguistic processing (Abney & Bird 2010). The focal data types, bilingual texts and lexicons, relate each language to a reference language. The ability to train systems to translate into and out of a given language is proposed as the yardstick for determining when that language is adequately documented. Bird will report on recent efforts to incorporate datasets built by the language resources community, via the "Language Commons". He will also describe a new project that is recording and transcribing material from a large number of unwritten languages in Papua New Guinea.

Steven Abney and Steven Bird (2010), The Human Language Project: Building a universal corpus of the World's languages, Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics.

A pdf version of the presentation is available.

Dr. Yaeger-Dror will discuss her recent work at LDC formulating coding conventions for speech archives in three areas: (1) coding for the social situation; (2) demographic coding that could be used as relevant research in future studies; and (3) the influence of interpersonal attitudes on speech variation. Most of the talk will center on this last point, focusing on the speakers' attitudes toward their interlocutors and how one might be able to go about determining this information without recourse to Gilesian psychological studies .

A pdf version of the presentation is available.

In this talk, Professor Kahana will discuss the major empirical phenomena concerning recall of common words and the theoretical issues raised by these phenomena. He will show how memory researchers have devised theories to explain these data and present some critical tests of those theories.

The modern Arabic colloquial dialects stand out in the world of dialectology and historical linguistics. Though all languages display dialectal variation, Arabic represents a special case -- attempts to classify and trace its varieties by standard linguistic techniques do not produce satisfactory results. It has been suggested (Versteegh, 1984) that this failure could be explained by positing that modern Arabic is a product of creolization. This study represents a focused, cross-dialectal examination of a single Arabic dialect area (Tunisia) in search of evidence of creolization and subsequent effects.

A PowerPoint version of the presentation is available as well as Leddy-Cecere's honors thesis, which was the basis for this presentation .

The introductory section of the talk presents the complex linguistic scenario of India and the role Sanskrit has to play in it. The next section discusses the language technology resources being developed at Jawaharlal Nehru University (JNU), New Delhi, the premier university of India for Sanskrit and other major Indian languages under Technology Development for Indian Languages (TDIL) - an initiative of the Indian government’s Department of Information Technology (DIT). The concluding section highlights the issues and challenges being faced and scope for future collaboration.

A pdf version of the presentation is available.

The topic of this session will be the Bibliotheca Alexandrina, Alexandria, Egypt. Guest speakers Professors Magdy Nagi and Ahmed Bhargout will discuss the library's holdings and the current Universal Networking Language project, respectively.

"Bibliotheca Alexandrina: The oldest library in the digital age"

Since its inauguration in 2002, Bibliotheca Alexandrina (BA) has devoted itself to be the center of excellence and the right platform to address the ever advancing technology of our time. This presentation sheds light on some of the initiatives of the BA, carried out by the International School of Information Science (ISIS), to document and preserve heritage through digital archives and to offer the right platform for advancing scientific research in addition to its digital initiatives to boost children's skills and to catalyze reform in the Arab world.

"Ibrahim Shihata Arabic UNL Center at Bibliotheca Alexandrina"

The Universal Networking Language (UNL) project is regarded as one of the most promising scientific research initiatives at the BA carried out by the ISIS. This presentation gives an overview on the history of the UNDL foundation which devises the program and its partnership with the BA. The presentation also gives a comprehensive overview of the UNL specifications, the software and system development at the BA including the UNL +3 engines and Knowledge Extraction System, and the tools deployed for the center. Moreover, the Book Catalogue is demonstrated as one of the applications on top of the UNL.

A PowerPoint version of Magdy Nagi's presentation is available.

The corpus of Supreme Court written opinions is a rich linguistic resource. Not only does this corpus provide a longitudinal sample of formal American English, but it is also a source of text with identified authors and vote-coded sentiment. Despite this value and years of qualitative and quantitative material of the United States Supreme Court, no compiled corpus of t hese opinions is currently available to researchers. The purpose of this talk is (1) to describe efforts to compile both the complete corpus of Supreme Court Opinions and associated metadata, (2) to outline a number of our current research projects utilizing this data, and (3) to discuss any criticism, potential projects, or possible collaboration.

A pdf version of the presentation is available.

Title and Instructor

Simon Hawkins is an assistant Professor of Anthropology at Franklin and Marshall College in Lancaster, PA. Professor Hawkins has studied language learning in Tunisia and will be sharing some aspects of that work. More information about Professor Hawkins can be found here.

ABSTRACT: Despite the convenient categorization of languages, particularly English, into national varieties, some specific discourses cross national and linguistic borders. For some of these varieties, such as academic writing and Internet conventions, what is linguistically important is not the language used, but the global discourses and language ideologies of which they are a part. Multilingual practices in Tunisia illustrate these examples.

Lunch will be provided. Hope to see you there!

Rushin Shah is a visiting scholar working at Penn and LDC this year. He received his bachelor's and master's degrees in Computer Science from the Indian Institute of Technology (IIT) Kharagpur. In addition to his work at LDC under the direction of Mark Liberman and Mohamed Maamouri, Rushin has worked on machine learning and named entity tagging systems with Lyle Ungar at Penn's department of Computer and Information Science.

ABSTRACT: The current process of Arabic corpus annotation at LDC relies on using the Standard Arabic Morphological Analyzer (SAMA) to generate various morphology and lemma choices, and supplying these to manual annotators who then pick the correct choice. However, a major constraint of this process is that SAMA can generate dozens of choices for each word, each of which must be examined by the annotator. Moreover, SAMA does not provide any information about the likelihood of a particular choice being correct. A system that ranks these choices in order of their probabilities, and manages to assign the highest or second-highest rank to the correct choice with a high degree of accuracy would hence be very useful in accelerating the rate of annotation of corpora. Such a system would also be able to aid intermediate Arabic language learners by creating annotated versions of news articles or other web pages submitted by them. We describe such a model that simultaneously performs morphological analysis and lemmatization for Arabic, using choices supplied by SAMA. We convert morphological labels into vectors of various morphosyntactic features, such as basic part-of-speech, gender, number, mood, prefixes, suffixes, case, etc. We then use these various attributes of the supplied Arabic data to create models for lemmas and MSFs, and combine these individual models into one aggregate model that simultaneously predicts lemmas and complete morphological analyses. Our model achieves accuracy in the high nineties. This is better than what prior approaches to this problem have been able to obtain, and it will allow us to not only significantly accelerate the corpus annotation process at LDC but also create an effective helper interface for Arabic language learners. In this presentation, I will discuss the problem, our approach to it, and the process of designing and creating the final model.

A PowerPoint version of this presentation is available:
Simultaneous Morphological Analysis and Lemmatization of Arabic Text

ABSTRACT: There has been a need for the present American Deaf communities to preserve a sample of their language so that they can appreciate the richness of their language for generations. There is also a practical need for materials that can be used in a wide variety of settings, ranging from American Sign Language (ASL) instruction for deaf children to training of people who work with deaf communities. This talk describes a long-term project that meets those needs, namely, the establishment of an ASL corpus by collecting a comprehensive and representative sample of ASL from around the nation. The talk opens with a description of other sign langauge corpora outside the U.S. that have been successful and then offers an outline of the ASL corpus project that is currently underway, including the kinds of data to be be collected and the methodology to be used for the data collection.

Title and Instructor

Shyam S. Agrawal. Shyam is the Executive Director of KIIT College of Engineering, Gurgaon, India and Advisor to the Centre for Development of Advanced Computing (CDAC), Noida, India.

ABSTRACT: In the past few decades there has been a pressing demand and need to develop speech and language corpora for training, testing and benchmarking of speech technology systems for various applications. Richly annotated corpora and labeled databases are needed to develop models of spoken languages and also to understand the structure of speech and the variability that occurs in the speech signals due to a variety of factors.

There are twenty-two official Languages and more than 300 dialects used in India. These languages have their specific structure and properties which have significant differences from European languages. This talk presents some of the phonetic differences in Hindi compared to English and presents an overview of the efforts made by CDAC, Noida and some other institutions to develop text and speech databases, tools, and some techniques for the processing of some Indian languages. For the collection of speech databases, issues and procedures related to text selection, e.g. multiform units and variables such as demographic, dialectal, environmental, emotional, linguistic background etc. have been included. Special tools developed for the analysis of text are described. The objective has been that tools should be adaptive to other Indian Languages and also to other languages.

Details of some of the application-oriented task specific databases such as the ELDA-sponsored database for Hindi and the CFSL Speaker Identification database for forensic applications will be described in detail.

A PowerPoint version of this presentation is available:
Development of Resources and Techniques for Processing of some Indian Languages

Title and Instructor

Introduction to existing resources for communicating your LDC projects over the web. The templates provide a professional, consistent and attractive design while allowing creativity and variation in each project's web site approach. The templates will help you define a predictable and organized navigation structure for LDC employees, project sponsors, research, and general visitors. Questions concerning use of the web standards, such as CSS and HTML, are encouraged throughout the presentation.

Title and Instructor

In this talk Walker seeks to reduce this gap by outlining the apparent problem and solution spaces; and by opening for discussion the utility of annotation scoring metrics in the various domains of empirical, computational and corpus linguistics -- and more cogently in the domain of quality control for linguistic data creation.

The talk will be organized into four main sections, followed by a brief discussion:

1. ACE Annotation: An Illustrative Introduction
2. Exploring the problem space
3. Exploring the solution space
4. Extending the metaphor: Building better linguistic data

Dr. Draxler will describe the Ph@ttSessionz web application and its major components, SpeechRecorder and WebTranscribe, and he will outline the infrastructure developed at BAS for WWW-based speech recordings. Dr. Draxler will also discuss the strategies employed to enlist schools in the project and present preliminary analyses of the Ph@ttSessionz speech database.

The Linguistic Data Consortium (LDC) has created large amounts of annotated linguistic data for a variety of evaluation programs and projects using highly customized annotation tools developed at the LDC. LDC programmers Kazuaki Maeda, Julie Medero and Haejoong Lee will discusses the history of annotation tool development at the LDC and share some of the approaches they are currently taking. Two tools in particular will be highlighted: (1) the LDC's model for decision point-based annotation and adjudication, which was used effectively in the ACE 2005 annotation effort; and (2) XTrans,a new speech transcription and annotation tool particularly suited for transcribing meeting speech that was used by the LDC in the NIST meeting recognition evaluation and Mixer Spanish and Russian telephone conversation studies.

Title and Instructor

.pdf, postscript and Powerpoint versions of this presentation are available.

Title and Instructor

Title and Instructor

Morphological analysis (word analysis) and generation are foundation technologies used in many kinds of natural-language processing, including dictionary lookup, language teaching, part-of-speech disambiguation (tagging), syntactic parsing, etc. Successful and publicly available software implementations based on "finite-state" theory include Koskenniemi's Two-Level Morphology, AT&T Lextools, Groningen University's Fsm Utils, and Xerox's lexc and xfst languages. The Xerox tools are now available on CD-ROM in a book entitled "Finite State Morphology", Beesley & Karttunen, 2003, CSLI Publications.

The talk will briefly and gently cover the history and underlying theory of finite-state morphology, and introduce lexc and xfst syntax.

Finite-state morphological analyzers are excellent projects for a Master's Thesis, and for field linguists they are a practical way to encode, computerize and test morphotactic grammars, alternation rules and lexicons that would otherwise remain inert on paper. Finite-state morphology has been successfully applied to languages around the world, including the obviously "commercial" European languages, Finnish, Hungarian, Basque, Turkish, Korean, Arabic, Syriac, Hebrew, several Bantu languages, a variety of American Indian languages, etc.

Beesley will also be available for consultation at the LDC 8-9 December.

The presentation will start from the early standardization of Arabic and lead to the emergence of 'diglossia' and its linguistic and sociolinguistic consequences. The dominant attitudes towards linguistic reforms will also be presented. The second focal point will be on the Arabic reading process, its challenges and its consequences for reading performance and for education in general.

In a connected second part of the same presentation, Tim Buckwalter will focus on the Arabic NLP Issues. He will then present his morphological analyzer and his lexicon. A brief overview of the LDC Arabic Treebank project will follow.

This presentation will discuss the various speech collection projects undertaken at the Linguistic Data Consortium at the University of Pennsylvania during the years 1995-present. Included will be a discussion of telephone speech data collection projects and on-site speech collection projects. Data collection projects covered in this talk will include: CallHome, CallFriend, Switchboard, ROAR and FISHER.

Data and Annotations for Sociolinguistics (DASL): Using digital data to address issues in sociolinguistic theory
Stephanie Strassel, Linguistic Data Consortium

A longstanding focus of sociolinguistic research has been the quantitative analysis of language variation and change, an endeavor that necessarily begins with the empirical observation and statistical description of linguistic behavior. Current technology encourages the collection and analysis of such data, and even the presentation and publication of research findings, wholly within the digital domain. Within the field of human language technology, such benchmark data has proven to be an essential ingredient for progress, as it reduces the cost of analytical infrastructure within research communities, frees researchers to focus on their interests, encourages collaboration and reduces impediments to new participants. However, most empirical data within sociolinguistics continues to be collected and analyzed by individuals or individual research groups, and is never made available to the wider research community. This proprietary approach to data hampers collaboration, the replication of studies and the comparison of models, methods and results, all necessary components of rigorous science. The prospect of digital data sharing in sociolinguistics also raises theoretical and methodological questions: Can sociolinguists make effective use of existing corpora? Do the insights gained from corpus data differ qualitatively from data most commonly used in quantitative sociolinguistics, namely recordings of sociolinguistic interviews? What are the best practices for the creation of new digital resources for sociolinguistic research?

The project on Data and Annotations for Sociolinguistics (DASL), currently underway at the Linguistic Data Consortium with support from NSF via the Talkbank project, begins to address these issues. DASL investigates the use of digital data in sociolinguistics through a series of case studies involving both analysis of variation in existing corpora and the creation of new data sets. This paper will introduce DASL's goals, assumptions, data and tools and will review annotation and corpus creation efforts and results to date.

Towards a Comprehensive, Empirical Analysis of Linguistic Data: the case of Regional Italian vowel systems

Any empirical study of language relies necessarily upon a body of observations of linguistic behavior even if the study fails to formally acknowledge its corpus. The decisions one makes in approaching data affect research profoundly by opening some avenues of inquiry while blocking others. Looking across research communities as diverse as sociolinguistics and speech technologies, one finds methods that may be integrated in order to both broaden research possibilities and to perform research more efficiently.

This presentation explores the relationship among data, tools, annotation (or coding) processes and the research they support. It will focus specifically on the quantitative analysis of linguistic variation. The data come from a series of sociolinguistic interviews undertaken to investigate the modeling of variation in the regional speech of central Italy.

After describing the motivation for this study, I will demonstrate a series of tools, processes and data formats that permit a comprehensive yet rapid analysis of vowel systems. Specifically, I will demonstrate tools for transcription and segmentation, lexicons and search tools that automatically select and categorize tokens of interest from the transcripts, batch processes that perform acoustic analyses of the selected tokens and an interface for managing and adding human judgments to these analyses. In the process I will offer a particular perspective on tool development, favoring information retention and annotator efficiency over computational efficiency and portability.

The tools and processes I will demonstrate were designed to interact with each other without losing precious information from the original audio such as the phonetic and lexical context of each vowel, the time and situation in which it was uttered, the demographic features of the speaker and so on. As a result, they make it possible or even trivial to explore issues that are otherwise impossible or at least difficult such as the interaction of phonological variation as a function of speech rate and time within an interview.

Title and Instructor

Over the past decade of creating and managing speech corpora, LDC staff have developed literally hundreds of utilities, user interfaces and file formats. These databases are becoming increasingly complex in their structure, with rich standoff annotations organized across multiple layers. At the same time, the range of contributing specialties has become more diverse, as illustrated by LDC's future publication plans in such areas as field linguistics, sociolinguistics, gesture, and animal communication.

In this talk I will outline the traditional corpus production process and catalog the problems we have experienced. This provides the backdrop for LDC's R&D effort over the last four years, which has created new software infrastructure and a suite of annotation tools. I will introduce the principles and key concepts of the annotation graph toolkit (AGTK), describe the current tools, and give a brief overview of the tool development process. Finally, I will introduce OLAC, the Open Language Archives Community, and demonstrate how it is being used for describing and discovering language resources of the kind we create at the LDC. The talk will be followed by an informal demonstration session.

More information about AGTK and OLAC is available at agtk.sf.net and www.language-archives.org.

Note: This presentation will be accessible to a general audience.

Developers of the work I will report include Kazuaki Maeda, Xiaoyi Ma, Haejoong Lee, Beth Randall, Salim Zayat, Craig Martell, Chris Osborn, John Breen, Jonathan Dick, Eva Banik, Alan Lee and Jonathan Wright.

A PDF version of this presentation is available:
New Methods for Constructing Annotated Speech Corpora

The objective of the ACE Program is to develop core automatic content extraction technology to enable text processing through the the detection and characterization of entities, relations, and events. As part of the DARPA TIDES program, ACE supports technology research and development for various classification, filtering, and selection applications by extracting and representing language content (i.e., the meaning conveyed by the data). The ultimate goal of ACE is the development of technologies that will automatically detect and characterize this meaning.

For the past three years, the Linguistic Data Consortium has been developing annotated corpora for the ACE program. Data for ACE consists of newspaper, newswire and broadcast news transcripts. To support Entity Detection and Characterization, ACE annotators label selected types of entities (Persons, Organizations, etc.) mentioned in text data. The textual references to these entities are then characterized and multiple entity mentions are co-referenced. The Relation Detection and Characterization task requires annotators to identify and characterize relations between the labeled set of entities. The LDC's role in ACE has recently expanded to encompass annotation of all data for the ACE program as well as development and maintenance of annotation guidelines and annotation tools.

In this talk, we describe corpus development for the ACE program, focusing on annotation procedures and guidelines as well as quality assurance measures. In addition, we touch on particular annotation challenges including classifying generic entities, metonymic entity mentions (including the concept of GeoPolitical Entities) and identifying the temporal attributes of relations.

A powerpoint version of this presentation is available:
Corpus Development for the ACE (Automatic Content Extraction)

What is a bilingual dictionary? Most of us have used bilingual dictionaries, so the answer seems obvious. But when it comes to defining the structure of a dictionary as a database on a computer, the obvious becomes non-obvious.

I will talk about the structure of a bilingual lexicon, and in particular that of a lexical entry, from a computational and linguistic viewpoint. There are (at least) three levels at which one might define such structure. Proceeding from the most concrete to the most abstract, these are: the file format level (e.g. in terms of an XML structure); a model (using a modeling language such as UML); and an ontology of concepts.

The talk will in fact begin with the abstract ontology and proceed to a model, which I have been developing in collaboration with several computational linguists in SIL (the Summer Institute of Linguistics). I will have little to say about the file format level. Some issues which arise include:

• The users of the lexicon (human users vs. computational linguistics systems, such as parsers)
• On-line vs. printed dictionaries
• Data integrity issues (what happens when you delete the lexical entry of a word that was the synonym of another lexical entry?)
• Modeling areas outside traditional lexicography, especially morphology
• Multi-dialectal lexicons

For the brave, a model for lexicons, morphology and other linguistic components is located at http://fieldworks.sil.org/ModelDoc/. (However, when I tried to go there today, the site was down.)

A powerpoint version of this presentation is available:
Modeling Lexical Entries in Bilingual Dictionaries

Virtually all text corpora are drawn from "found" data -- material that already exists in electronic form to serve some purpose other than corpus-based language research, such as: publication of books, periodicals or daily news; archival preservation of public, commercial or government transactions; online discussions on various topics among diverse interest groups; and so on. The problem is that each data source has its own unique set of needs and conventions that dictate the data formats used to store and transport its particular content -- as well as its own rate of failure in making sure the data satisfy its needs and conventions.

The task for the LDC, working on behalf of corpus researchers, is to design and apply the tools needed to distill each source into a common, standardized form that will (1) maximize the usability of the data on any researcher's chosen computer system, (2) preserve as much information as possible from the source, and (3) discard as much interference and noise as possible -- and do all this with a minimum
of manual effort. The present talk will discuss strategies and tools that have been developed and used at LDC over the years for this purpose.

BITS and other Machine Translation Collection Projects
Xiaoyi Ma, Mark Y. Liberman

Parallel corpus are valuable resource for machine translation, multi-lingual text retrieval, language education and other applications, but for various reasons, its availability is very limited at present. Noticed that the World Word Web is a potential source to mine parallel text, researchers are making their efforts to explore the Web in order to get a big collection of bitext. This paper presents BITS
(Bilingual Internet Text Search), a system which harvests multilingual texts over the World Wide Web with virtually no human intervention. The technique is simple, easy to port to any language pairs, and with high accuracy. The results of the experiments on German - English pair proved that the method is very successful.

Postscript and .pdf versions of this paper are available.

Our goal is qualitatively better methods for automatically extracting information from the biomedical literature, relying on recent progress and new research in three areas: high-accuracy parsing, shallow semantic analysis, and integration of large volumes of diverse data. We are focusing initially on two applications: drug development, in collaboration with researchers in the Knowledge Integration and Discovery Systems group at GlaxoSmithKline, and pediatric oncology, in collaboration with researchers in the eGenome group at Children's Hospital of Pennsylvania. These applications, worthwhile in their own right, provide excellent test beds for broader research efforts in natural language processing and data integration.

In particular, we propose to develop and test new general methods for information extraction from text, based on on-going research at Penn in corpus-based algorithms for parsing, predicate-argument analysis and reference resolution. We will collaborate with groups led by Robert Gaizauskas at the University of Sheffield (UK) and by Jun-ichi Tsujii at the University of Tokyo (Japan), as well as with the GSK and CHOP groups, in applying these general methods to particular problems in biomedical information extraction. The GSK group has already made effective use of the best available information-extraction technology, so that the new techniques can be assessed in the drug-development application for their added value relative to the state of the art.

To give a simple, concrete example, we want a program that will read a phrase like

Amiodarone weakly inhibited CYP2C9, CYP2D6, and CYP3A4-mediated activities with Ki values of 45.1--271.6 μM

and add to a database a set of entries whose ordinary-language presentation is

amiodarone inhibits CYP2C9 with Ki=45.1--271.6
amiodarone inhibits CYP2D6 with Ki=45.1--271.6
amiodarone inhibits CYP3A4 with Ki=45.1--271.6

This project will also address several database research problems, including methods for modeling complex, incomplete and changing information using semistructured data, and also ways to connect the text analysis process to an information integration environment that can deal with the wide variety of extant bioinformatic data models, formats, languages and interfaces. Such problems are central to current database research at Penn. Our work will build on the progress represented by Penn's K2/Kleisli data integration environment, by extending it to deal with semi-structured data. This will be important managing the information that is extracted, and also in making use of the many specialized data resources that can be brought to bear in generating the high-accuracy text analysis required to extract the information effectively in the first place. Because the K2/Kleisli system is widely used in bioinformatics applications, and in particular has been used for several years at GSK, these extensions will facilitate collaboration with biomedical researchers as well as supporting the IE research itself.

The engine of recent progress in language processing research has been linguistic data: text corpora, treebanks, lexicons, test corpora for information retrieval and information extraction, and so on. Much of this data has been created by Penn researchers and published by Penn's Linguistic Data Consortium. As part of the proposed project, we will develop and publish new linguistic resources in three categories: a large corpus of biomedical text annotated with syntactic structures (Treebank) and shallow semantic structures ("proposition bank" or Propbank); a large set of biomedical abstracts and full-text articles annotated with entities and relations of interest to researchers, such as enzyme inhibition by various compounds, or genotype/phenotype connections (Factbanks); and broad-coverage lexicons and tools for the analysis of biomedical texts.