This resource is the second version of an Italian morphological dictionary for content words, encoded in a JSON Lines format text file. It contains correspondences between surface form and lexical forms of words followed by standard grammatical properties. Compared to the first release, this version has a better JSON structure. The surface word forms have been generated algorithmically by using stable phonological and morphological rules of the Italian language. Particular attention has been given to the generation of verbs for which rules have been extracted from A.L e G. Lepschy, La Lingua Italiana. The dictionary with its remarkable coverage is particularly useful used together with the Italian Function Words v2 (http://hdl.handle.net/11372/LRT-2629) for tasks such as pos-tagging or syntactic parsing.
This resource is the third version of the Italian morphological dictionary for content words (http://hdl.handle.net/11372/LRT-2630), encoded in a JSON Lines format. Compared to the previous version, it contains some minor improvements.
This dictionary is a curated list of Italian function words in a JSON Lines format text file, particularly useful for tasks such as POS-Tagging or Syntactic Parsing. It contains 999 single-word forms and 2501 multi-words forms. Each entry may have the following grammatical features: lemma, pos, mood, tense, person, number, gender, case, degree.
This dictionary is the second version of 11372/LRT-2288, a curated list of Italian function words in a JSON Lines format text file, particularly useful for tasks such as POS-Tagging or Syntactic Parsing. It contains 999 single-word forms and 2501 multi-words forms. Each entry may have the following grammatical features: lemma, pos, mood, tense, person, number, gender, case, degree. Compared to the first release, this version has a more clear JSON structure.
This dictionary is the third version of 11372/LRT-2288, a curated list of Italian function words in a JSON Lines format text file, particularly useful for tasks such as part of speech tagging or syntactic parsing. Compared to the previous release, this version includes some minor improvements.
Text preprocess (this preprocess service requires that the input text be in plain text format (file .txt) and UTF-8).
Basically, it carries out: (i) text segmentation into minor structural units (titles, paragraphs, sentences, etc.); (ii) detection of entities not found in dictionaries (numbers, abbreviations, URLs, emails, proper nouns, etc.); and (iii) the keeping of sequences of two or more words in a single block (dates, phrases, proper nouns, etc.).
POS tagger. (The input file must be in plain text format (file.txt) and UTF-8 encoded. The disambiguation process is done by a TreeTagger instance trained by the IULA.)