ILSP Sample Clauses

ILSP. ILSP has the following resources and tools available for Greek. Required resources and tools Available resources and tools Comments Raw corpora (min. 100 occurrences per verb) yes Text processing tools: tagger tokeniser lemmatiser shallow parser/chunker yes Subcat classifier no Lexical builder no Filter no Evaluation resources (SCF yes dictionaries) Tools Available resources and tools that will be utilized are: - large (100 mws) general domain corpora, - a tool processing chain developed at ILSP that consists of a tokeniser, a tagger, a lemmatizer and a shallow parser, Evaluation resources - LEXIS, a Greek computational lexicon of general language created from a general language corpus, which comprises approximately 69,000 entries containing morphological information, of which a subset of 32,000 entries also contains syntactic information and a further subset of 15,000 includes semantic information. The syntactic level contains around 8,000 verbal syntactic units, all bearing subcat information: information is provided as regards the number of complements that each syntactic unit can subcategorise for, as well as their identification, i.e. their syntactic function, morphosyntactic realisation and optionality The LEXIS lexicon is an extension of the PAROLE/ SIMPLE lexica as regards the size, but also as regards the model as such, in order to cater for the idiosyncrasies of the Greek language. This lexicon will serve as validation resource against which the subcat frames acquired from the corpora will be validated. References
Sample 1
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ILSP. Since ILSP does not have an SCF acquisition tool for Greek, we plan to develop one by first examining portability of algorithms developed by partners in the consortium. We plan to initially use a general domain corpus of 100+M EL corpus, and an existing subcat frame lexicon for evaluation on a small set of verbs. After that we will examine tuning this tool to one of the two domains targeted by the project, by a) selecting or, creating manually, entries for 20-30 verbs in the domain and b) extract SCF information from a small EL corpus in the domain.
Sample 1

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