This resource is 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 grammatical features. 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 the famous A.L e G. Lepschy, La lingua italiana. The dictionary with its remarkable coverage is particularly useful used together with the Italian Function Words (http://hdl.handle.net/11372/LRT-2288) for tasks such as POS-Tagging or Syntactic Parsing.
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.
This package contains data used in the IWPT 2020 shared task. It contains training, development and test (evaluation) datasets. The data is based on a subset of Universal Dependencies release 2.5 (http://hdl.handle.net/11234/1-3105) but some treebanks contain additional enhanced annotations. Moreover, not all of these additions became part of Universal Dependencies release 2.6 (http://hdl.handle.net/11234/1-3226), which makes the shared task data unique and worth a separate release to enable later comparison with new parsing algorithms. The package also contains a number of Perl and Python scripts that have been used to process the data during preparation and during the shared task. Finally, the package includes the official primary submission of each team participating in the shared task.
This package contains data used in the IWPT 2021 shared task. It contains training, development and test (evaluation) datasets. The data is based on a subset of Universal Dependencies release 2.7 (http://hdl.handle.net/11234/1-3424) but some treebanks contain additional enhanced annotations. Moreover, not all of these additions became part of Universal Dependencies release 2.8 (http://hdl.handle.net/11234/1-3687), which makes the shared task data unique and worth a separate release to enable later comparison with new parsing algorithms. The package also contains a number of Perl and Python scripts that have been used to process the data during preparation and during the shared task. Finally, the package includes the official primary submission of each team participating in the shared task.