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STW Thesaurus for Economics is now available under http://zbw.eu/stw. STW is a richly interconnected vocabulary in English and German on economics and business economics as well as some related subject areas. It includes subject categories and lots of synonyms in order to find the appropriate terms. Its publication aims at providing an interlinking hub for economics resources on the web of Linked Data. The thesaurus is maintained by the German National Library of Economics (ZBW) and published under a Creative Commons (by-nc-sa) license. It is delivered as XHTML+RDFa pages with an incremental search interface and a navigatable tree. A SKOS RDF/XML dump version can be downloaded, as well as a set of links to dbpedia concepts. More information about the design of the application can be found in a paper for the "Linked Data on the Web" workshop in Madrid (http://events.linkeddata.org/ldow2009/papers/ldow2009_paper7.pdf).

SemLink is a project whose aim is to link together different lexical resources via a set of mappings. These mappings will make it possible to combine the different information provided by these different lexical resources for tasks such as inferencing. We also plan to use the mappings to aid in semi-automatic extension of each resources coverage, to increase the overall overlap in coverage. Currently, we are creating mappings between the following resources: * PropBank: A corpus of one million words of English text, annotated with argument role labels for verbs; and a lexicon defining those argument roles on a per-verb basis. * VerbNet: A lexicon that groups verbs based on their semantic/syntactic linking behavior. * FrameNet: A lexicon based on frame semantics. * WordNet: A lexicon that describes semantic relationships (such as synonymy and hyperonymy) between individual words. The content of all four of these resources can be browsed on-line using the Unified Verb Index. A presentation giving an introduction to SemLink, and two of the resources it combines (PropBank and VerbNet), was given at the SIGSEM/ISO workshop held jointly with the IWCS-7 conference.

The SemCor corpus The SemCor corpus, created by the Princeton University, is a subset of the English Brown corpus containing almost 700,000 running words. In SemCor all the words are tagged by PoS, and more than 200,000 content words are also lemmatized and sense-tagged according to Princeton WordNet 1.6. More in detail, the SemCor corpus is composed of 352 texts. In 186 texts all the open class words (nouns, verbs, adjectives, and adverbs) are annotated with PoS, lemma and sense, while in the remaining 166 texts only verbs are annotated with lemma and sense. The "all-words" component of SemCor has 359,732 tokens among which 192,639 are semantically annotated, while the "only-verbs" component has 316,814 tokens among which 41,497 verb occurrences are semantically annotated. Different versions of SemCor are available for downloading here. Related Publications: 1. Landes S., Leacock C., and Tengi, R.I. (1998) "Building semantic concordances". In Fellbaum, C. (ed.) (1998) WordNet: An Electronic Lexical Database. Cambridge (Mass.): The MIT Press. 2. Fellbaum, C., Grabowski, J. and Landes, S. (1998). "Performance and confidence in a semantic annotation task". In Fellbaum, C. (ed.) (1998) WordNet: An Electronic Lexical Database. Cambridge (Mass.): The MIT Press. 3. Fellbaum, C. (ed.) (1998) WordNet: An Electronic Lexical Database. Cambridge (Mass.): The MIT Press.

Medical Subject Headings (MeSH) is a huge controlled vocabulary (or metadata system) for the purpose of indexing journal articles and books in the life sciences. Created and updated by the United States National Library of Medicine (NLM), it is used by the MEDLINE/PubMed article database and by NLM's catalog of book holdings. MeSH can be browsed and downloaded free of charge on the Internet. The yearly printed version was discontinued in 2007.