linguistics because they lacked sufficient syntactic and semantic information for computer programs. The work on computational lexicology quickly led to efforts in two additional directions. Successors to Computational Lexicology First, collaborative activities between computational linguists and lexicographers led to an understanding of the role that corpora played in creating dictionaries. Most computational lexicologists moved on to build large corpora to gather the basic data that lexicographers had used to create dictionaries. The ACL/DCI (Data Collection Initiative) and the LDC (Linguistic Data Consortium) went down this path. The advent of markup languages led to the creation of tagged corpora that could be more easily analyzed to create computational linguistic systems. Part-of-speech tagged corpora and semantically tagged corpora were created in order to test and develop POS taggers and word semantic disambiguation technology. The second direction was toward the creation of Lexical Knowledge Bases (LKBs). A Lexical Knowledge Base was deemed to be what a dictionary should be for computational linguistic purposes, especially for computational lexical semantic purposes. It was to have the same information as in a print dictionary, but totally explicated as to the meanings of the words and the appropriate links between senses. Many began creating the resources they wished dictionaries were, if they had been created for use in computational analysis. WordNet can be considered to be such a development, as can the newer efforts at describing syntactic and semantic information such as the FrameNet work of Fillmore. Outside of computational linguistics, the Ontology work of artificial intelligence can be seen as an evolutionary effort to build a lexical knowledge base for AI applications. Standardization Optimizing the production, maintenance and extension of computational lexicons is one of the crucial aspects impacting NLP. The main problem is the interoperability: various lexicons are frequently incompatible. The most frequent situation is: how to merge two lexicons, or fragments of lexicons? A secondary problem is that a lexicon is usually specifically tailored to a specific NLP program and has difficulties being used within other NLP programs or applications. To this respect, the various data models of Computational lexicons are studied by ISO/TC37 since 2003 within the project lexical markup framework leading to an ISO standard in 2008. References Amsler, Robert A. 1980. Ph.D. Dissertation, "The Structure of the Merriam-Webster Pocket Dictionary". The University of Texas at Austin. External links Computational lexicology issue in ACL Wiki 1.ACL Wiki 2.Association for Computational Linguistics, Official