An Interoperability Challenge for the NLP Community

Transcription

1 An Interoperability Challenge for the NLP Community Nancy Ide 1 and James Pustejovsky 2 1 Vassar College and 2 Brandeis University, USA Web services are becoming increasingly more sophisticated and responsive to user needs over a range of applications and areas. However, at this time a robust, interoperable software infrastructure to support natural language processing (NLP) research and development does not exist. The need for robust language processing capabilities across academic disciplines, education, and industry is without question of vital importance. The goals of our NSF-funded SILT project, which has worked together with European and Asian collaborators, has been to advance interoperability among NLP tools and resources. The ultimate goal of this research is to build on the foundation laid in SILT and other projects, to create the momentum toward establishing a comprehensive network of Language Apps (LAPPs) web services and resources within the NLP community. To this end, in this talk, we define a shared task for the NLP community we call "The SILT Interoperability Challenge", which will call for development of interoperable web services. We anticipate that the challenge will be carried out in two or three iterations over the next two years.

2 Community Co-Creation in Cultural Domain Virach Sornlertlamvanich National Electronics and Computer Technology Center (NECTEC), Thailand Introduction Under the collaboration between Ministry of Culture and Ministry of Science and Technology by National Electronics and Computer Technology Center (NECTEC), a collection of cultural knowledge has been embodied since We did not start the work from scratch. Actually the work has been done some years ago by forming a set of servers individually operated by each province. Each province has to take care of their own contents about their responsible area. The initiative has been carried out for the purpose of creating a reference site of the local cultural knowledge. The distributed system is an aim to decentralize the management and to maintain the uniqueness of each specific area. However, there is a trade-off between the independent design and cost of maintenance that covers the service operation, interoperability and integrity. There are currently 77 provinces in Thailand, and each province is allocated an office for provincial cultural center. With the approach of the above mentioned distributed system, it is too costly to maintain the service and the standard for data interchange. The newly designed platform-based approach for digital cultural communication has been introduced. It is to build a co-creative relationship between the cultural institution and the community by using new media to produce audience-focused cultural interactive experience (Russo and Watkins 2005). First, we collected the existing provincial cultural knowledge and convert them to conform to a standardized set of metadata. This is to prepare the cultural knowledge for an open data schema and interoperability. The metadata is defined to follow the Dublin Core Metadata Element Set with some additional element to fulfill the requirement information during the recording process. Second, we assign representatives from each province and train them to be a core cultural content development team for community co-creation. The contributed content needs to be approved by the core team before public visibility. Third, the cultural knowledge will be put on service to the audience of such scholars who may be interested in the cultural practice, or business developers who may benefit from attaching the cultural knowledge to their products, or tourists who may seek for cultural tourism. This cultural media assets will be linked and annotated by a governed conceptual scheme such as Asian WordNet (Sornlertlamvanich and et al. 2009). The semantic annotated and linked data will be serviced as a fine-grained cultural knowledge for higher level applications. The new media for recording the cultural knowledge is in the form of narrative, photo, video, animation, image incorporated with GPS data for visualization on the map. Cultural Knowledge Co-Creation The existing cultural data has been collected and cleaned up to conform to the designated standard metadata. The absent data are supposed to be revised and augmented by the experts from the Ministry of Culture. A few tens of thousands of records have been collected but most of them are captured in a coarse-grained image. Narratives and images are revised by a group of trained expert to create a seed of standardized annotated cultural knowledge base. Some new records have been added together with animation, video, panoramic photograph, etc. New technique in capturing the

3 cultural image is aggressively introduced to create value added and gain more interest from the audience. The standardized annotated cultural knowledge base is presented through a set of viewing utilities to the audience. Filter according to the location and province is prepared for customizing to page for each province. This is to allow the unique presentation of each province. The administration of each province will be responsible to its content correctness and coverage. Actually, the attractive presentation and narrative are required to attract the audience. Figure 1 Community Co-Creation Cultural Knowledge Base Social networking system is introduced to invite the participation from the communities. The institution representatives are actively encouraged to create their own community. The results from the community co-creation will keep the content maintained and clean up to compete with each other. It is significantly that the provided framework can encourage the data accumulation and fulfill the needs from the audience. Community co-creation will feedback the actual requirement that can improve the quality of the content. Institution plays an important role in mediating between community and the audience. As a result, the multiple types of content are generated on a designated standard. The annotated metadata can be used as a guidance for higher level of data manipulation such as semantic annotation, cross language and link analysis. Reference: Russo, A. and Watkins, J Digital Cultural Communication: Audience and Remediation in Theorizing Digital Cultural Heritage eds. F. Cameron and S. Kenderdine, Cambridge, Mass., MIT Press. Sornlertlamvanich, V., Charoenporn, T., Robkop, K., Mokarat, C. and Isahara, H Review on Development of Asian WordNet in JAPIO 2009 Year Book, Japan Patent Information Organization, Tokyo, Japan.

4 Imagine we have 100 Billion Translated Words at our Disposal Jaap van der Meer TAUS Data Association Not just anonymous words scraped from numerous web sites, but good quality translations from trusted sources, from government bodies and institutions, from companies large and small and from professional translators. What could we do with it? We could transform the translation industry! Here is how we do it: 1. Terminology mining and dictionary building Today glossaries are built by terminologists: the best in class language specialists. It is laborious work and frustrating. Because language keeps changing, the terminologist is always behind and the glossary is often ignored. Imagine we have 100 billion translated words at our disposal. Terminology is harvested real-time. Synonyms and related terms are identified automatically. Part-of-speech is tagged, context is listed, sources are quoted, meanings are described. It is not rocket science. In fact all the tools exist to do this and do this well. 2. Customize automated translation Today we use MT on the internet and accept the stupid failures due to lack of domain knowledge of the engines. Some of us go through the lengthy and costly process of customizing an engine for our company s use. Imagine we have 100 billion translated words at our disposal. We will do fully automatic semantic clustering to find the translations that match our own domain. We will do automatic genre identification to make sure that we use the right style. We will go deeper in advancing the MT technology with syntax and concept descriptions. 3. Global market and customer analytics Today translation is an isolated function and cost center in most companies and organizations. We push translations out but we have no means to listen, learn and connect with our customers worldwide. Imagine we have 100 billion translated words at our disposal. We will integrate our translation process and skills with text analytics and social media management. We will do multilingual sentiment analysis, search engine optimization, opinion mining, customer engagement, competitive analytics, etcetera. From a cost center the translation function is now becoming a very valuable strategic ally in every global organization. 4. Quality management

5 Today we struggle to deliver adequate quality in translations. We miss the local flavor, the right term or the subject knowledge. The source texts may be in bad shape causing all kinds of trouble for the translator or the MT engine. The craftsmanship typical of the translation industry stops all innovation. Imagine we have 100 billion translated words at our disposal. We will automatically clean and improve source texts for translation. We will run automatic scoring and benchmarks on quality. We will improve consistency and comprehensibility. 5. Interoperability Today the lack of interoperability and compliance with standards costs a fortune. Buyers and providers of translation lose 10% to 40% of their budgets or revenues because language resources are not stored in compatible standard formats. Imagine we have 100 billion translated words at our disposal. Imagine that it s common practice in the global translation industry to share most of your public translation data in a common industry repository. Very naturally then all vendors and translation tools are driven towards hundred percent compatibility. Jobs and resources will travel without any loss of value. Benefits on an industry scale add up to billions of dollars or euros. Stakes are high. Risks are low. Only fear can stop us. A quarter of a million professional translators produce 625 million good quality translations every day, some 150 billion a year, of which an estimated 70% is published on the internet. We can collect and share 100 billion translated words every year. We should give unlimited access to this gigantic supercloud of translations. The translation supercloud must be not-for-profit and directed by the data contributors. The stakes are high. The translation industry will flourish. The world will communicate better across all language barriers. The risks are low. It is just a choice to participate proactively, or leave it to the pirates to change the industry. Only fear can stop us. Fear to change and fear to lose control will be replaced by fear to be left behind. Because many of the leaders have already started sharing their translations since July 2008 in the TDA repository.

6 U-Compare: Interoperability of Text Mining Tools with UIMA Sophia Ananiadou 1, Yoshinobu Kano 2 1 University of Manchester, UK and 2 Database Center for Life Science (DBCLS), Japan Due to the increasing number NLP resources (software tools and corpora), interoperability issues are becoming significant obstacles to effective use. UIMA, the Unstructured Information Management Architecture, is an open framework designed to aid in the construction of more interoperable tools. U-Compare is built on top of the UIMA framework, and provides both a concrete framework for out-of-the-box text mining and a sophisticated evaluation platform allowing users to run specific tools on any target text, generating both detailed statistics and instance-based visualizations of outputs. U-Compare is a joint project, providing the world's largest collection of UIMA resources that are compatible with a single, shared type system. The collection includes resources developed by different groups for a variety of domains. Whilst the current emphasis is on English biomedical text processing components, planned work within META-NET will significantly increase the inventory of components available for several European languages, including multi-lingual components. Japanese components are also in development. U-Compare can be launched straight from the web, without needing to be manually installed. All U-Compare components are provided ready-to-use and can be combined into workflows easily via a drag-and-drop interface without any programming. External UIMA components can also simply be mixed with U-Compare components, without distinguishing between locally and remotely deployed resources.

7 Opening, sharing, re-using language resources : who, what, when, where and how Stelios Piperidis Institute for Language and Speech Processing, Athena Research Center, Greece In its report titled Riding the Wave: how Europe can gain from the raising tide of scientific data, October 2010, the High-Level Group on Scientific Data states : A fundamental characteristic of our age is the raising tide of data global, diverse, valuable and complex. In the realm of science, this is both an opportunity and a challenge. In the context of language research and technology, the essence of this statement has been in focus for the last two decades. The current prevailing methodologies in language technology development, the sheer number of languages and the vast volumes of digital content together with a wide palette of useful content processing applications, render new models for managing the underlying language resources indispensable. META-SHARE tries to respond to this need by building a network of distributed repositories of language resources, including language data and basic language processing tools (e.g. morphological analysers, pos taggers, etc). Repositories bear a local or non-local (central) role. Local repositories are set up and maintained by organisations participating in the META-SHARE network, storing their own resources. Non-local (central) repositories are also set up and maintained by organisations participating in the META-SHARE network acting as storage and documentation facilities for resources either developed in organisations not wishing to set up their own repository, or they are donated or they are considered orphan resources, etc. Language resources are described according to a metadata schema (the META-SHARE metadata schema). Actual resources and their metadata reside in the local repositories, which export metadata records and allow their harvesting. Central network servers harvest, host and mirror META-SHARE s metadata and point to local repositories for browsing, downloading, etc actual resources. Users (language resources seekers/consumers) will be able to log-in once, search the central inventory using multifaceted search facilities and access the actual resources by visiting the resources repositories for browsing and downloading them, as well as getting additional information about the usage of specific resources, their relation (e.g. compatibility, suitability) to other resources, recommendations, etc. In this brief presentation, I will discuss the background of the emerging infrastructure, e.g. community needs this infrastructure should cater for, form and modes of operation, as well as instruments foreseen to help achieve maximum usability and sustainability. We will discuss the principles that META-SHARE uses regarding language resource sharing and the instruments that support them. We will conclude by elaborating on potential synergies with neighbouring initiatives and future plans at large.