DeriNet is a lexical network which models derivational relations in the lexicon of Czech. Nodes of the network correspond to Czech lexemes, while edges represent derivational relations between a derived word and its base word. The present version, DeriNet 1.5, contains 1,011,965 lexemes (sampled from the MorfFlex dictionary) connected by 785,543 derivational links. Besides several rather conservative updates (such as newly identified prefix and suffix verb-to-verb derivations as well as noun-to-adjective derivations manifested by most frequent adjectival suffixes), DeriNet 1.5 is the first version that contains annotations related to compounding (compound words are distinguished by a special mark in their part-of-speech labels).
DeriNet is a lexical network which models derivational relations in the lexicon of Czech. Nodes of the network correspond to Czech lexemes, while edges represent derivational relations between a derived word and its base word. The present version, DeriNet 1.6, contains 1,027,832 lexemes (sampled from the MorfFlex dictionary) connected by 803,404 derivational links. Furthermore, starting with version 1.5, DeriNet contains annotations related to compounding (compound words are distinguished by a special mark in their part-of-speech labels).
Compared to version 1.5, version 1.6 was expanded by extracting potential links from dictionaries available under suitable licences, such as Wiktionary, and by enlarging the number of marked compounds.
DeriNet is a lexical network which models derivational relations in the lexicon of Czech. Nodes of the network correspond to Czech lexemes, while edges represent derivational or compositional relations between a derived word and its base word / words. The present version, DeriNet 2.0, contains 1,027,665 lexemes (sampled from the MorfFlex dictionary) connected by 808682 derivational and 600 compositional links.
Compared to previous versions, version 2.0 uses a new format and contains new types of annotations: compounding, annotation of several morphological and other categories of lexemes, identification of root morphs of 244,198 lexemes, semantic labelling of 151,005 relations using five labels and identification of 13 fictitious lexemes.
DeriNet is a lexical network which models derivational relations in the lexicon of Czech. Nodes of the network correspond to Czech lexemes, while edges represent word-formational relations between a derived word and its base word / words. The present version, DeriNet 2.1, contains 1,039,012 lexemes (sampled from the MorfFlex CZ 2.0 dictionary) connected by 782,814 derivational, 50,533 orthographic variant, 1,952 compounding, 295 univerbation and 144 conversion relations.
Compared to the previous version, version 2.1 contains annotations of orthographic variants, full automatically generated annotation of affix morpheme boundaries (in addition to the roots annotated in 2.0), 202 affixoid lexemes serving as bases for compounding, annotation of corpus frequency of lexemes, annotation of verbal conjugation classes and a pilot annotation of univerbation. The set of part-of-speech tags was converted to Universal POS from the Universal Dependencies project.
EnTam is a sentence aligned English-Tamil bilingual corpus from some of the publicly available websites that we have collected for NLP research involving Tamil. The standard set of processing has been applied on the the raw web data before the data became available in sentence aligned English-Tamil parallel corpus suitable for various NLP tasks. The parallel corpus includes texts from bible, cinema and news domains.
HamleDT 2.0 is a collection of 30 existing treebanks harmonized into a common annotation style, the Prague Dependencies, and further transformed into Stanford Dependencies, a treebank annotation style that became popular recently. We use the newest basic Universal Stanford Dependencies, without added language-specific subtypes.
HamleDT (HArmonized Multi-LanguagE Dependency Treebank) is a compilation of existing dependency treebanks (or dependency conversions of other treebanks), transformed so that they all conform to the same annotation style. This version uses Universal Dependencies as the common annotation style.
Update (November 1017): for a current collection of harmonized dependency treebanks, we recommend using the Universal Dependencies (UD). All of the corpora that are distributed in HamleDT in full are also part of the UD project; only some corpora from the Patch group (where HamleDT provides only the harmonizing scripts but not the full corpus data) are available in HamleDT but not in UD.
HinDialect: 26 Hindi-related languages and dialects of the Indic Continuum in North India
Languages
This is a collection of folksongs for 26 languages that form a dialect continuum in North India and nearby regions.
Namely Angika, Awadhi, Baiga, Bengali, Bhadrawahi, Bhili, Bhojpuri, Braj, Bundeli, Chhattisgarhi, Garhwali, Gujarati, Haryanvi, Himachali, Hindi, Kanauji, Khadi Boli, Korku, Kumaoni, Magahi, Malvi, Marathi, Nimadi, Panjabi, Rajasthani, Sanskrit.
This data is originally collected by the Kavita Kosh Project at http://www.kavitakosh.org/ . Here are the main characteristics of the languages in this collection:
- They are all Indic languages except for Korku.
- The majority of them are closely related to the standard Hindi dialect genealogically (such as Hariyanvi and Bhojpuri), although the collection also contains languages such as Bengali and Gujarati which are more distant relatives.
- They are all primarily spoken in (North) India (Bengali is also spoken in Bangladesh)
- All except Sanksrit are alive languages
Data
Categorising them by pre-existing available NLP resources, we have:
* Band 1 languages : Hindi, Panjabi, Gujarati, Bengali, Nepali. These languages already have other large standard datasets available. Kavita Kosh may have very little data for these languages.
* Band 2 languages: Bhojpuri, Magahi, Awadhi, Braj. These languages have growing interest and some datasets of a relatively small size as compared to Band 1 language resources.
* Band 3 languages: All other languages in the collection are previously zero-resource languages. These are the languages for which this dataset is the most relevant.
Script
This dataset is entirely in Devanagari. Content in the case of languages not written in Devanagari (such as Bengali and Gujarati) has been transliterated by the Kavita Kosh Project.
Format
The dataset contains a single text file containing folksongs per language. Folksongs are separated from each other by an empty line. The first line of a new piece is the title of the folksong, and line separation within folksongs is preserved.
HinDialect: 26 Hindi-related languages and dialects of the Indic Continuum in North India
Languages
This is a collection of folksongs for 26 languages that form a dialect continuum in North India and nearby regions.
Namely Angika, Awadhi, Baiga, Bengali, Bhadrawahi, Bhili, Bhojpuri, Braj, Bundeli, Chhattisgarhi, Garhwali, Gujarati, Haryanvi, Himachali, Hindi, Kanauji, Khadi Boli, Korku, Kumaoni, Magahi, Malvi, Marathi, Nimadi, Panjabi, Rajasthani, Sanskrit.
This data is originally collected by the Kavita Kosh Project at http://www.kavitakosh.org/ . Here are the main characteristics of the languages in this collection:
- They are all Indic languages except for Korku.
- The majority of them are closely related to the standard Hindi dialect genealogically (such as Hariyanvi and Bhojpuri), although the collection also contains languages such as Bengali and Gujarati which are more distant relatives.
- All except Nepali are primarily spoken in (North) India
- All except Sanksrit are alive languages
Data
Categorising them by pre-existing available NLP resources, we have:
* Band 1 languages : Hindi, Marathi, Punjabi, Sindhi, Gujarati, Bengali, Nepali. These languages already have other large datasets available. Since Kavita Kosh focusses largely on Hindi-related languages, we may have very little data for these other languages in this particular dataset.
* Band 2 languages: Bhojpuri, Magahi, Awadhi, Brajbhasha. These languages have growing interest and some datasets of a relatively small size as compared to Band 1 language resources.
* Band 3 languages: All other languages in the collection are previously zero-resource languages. These are the languages for which this dataset is the most relevant.
Script
This dataset is entirely in Devanagari. Content in the case of languages not written in Devanagari (such as Bengali and Gujarati) has been transliterated by the Kavita Kosh Project.
Format
The data is segregated by language, and contains each folksong in a different JSON file.