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.
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.
Texts
The Prague Czech-English Dependency Treebank 2.0 (PCEDT 2.0) is a major update of the Prague Czech-English Dependency Treebank 1.0 (LDC2004T25). It is a manually parsed Czech-English parallel corpus sized over 1.2 million running words in almost 50,000 sentences for each part.
Data
The English part contains the entire Penn Treebank - Wall Street Journal Section (LDC99T42). The Czech part consists of Czech translations of all of the Penn Treebank-WSJ texts. The corpus is 1:1 sentence-aligned. An additional automatic alignment on the node level (different for each annotation layer) is part of this release, too. The original Penn Treebank-like file structure (25 sections, each containing up to one hundred files) has been preserved. Only those PTB documents which have both POS and structural annotation (total of 2312 documents) have been translated to Czech and made part of this release.
Each language part is enhanced with a comprehensive manual linguistic annotation in the PDT 2.0 style (LDC2006T01, Prague Dependency Treebank 2.0). The main features of this annotation style are:
dependency structure of the content words and coordinating and similar structures (function words are attached as their attribute values)
semantic labeling of content words and types of coordinating structures
argument structure, including an argument structure ("valency") lexicon for both languages
ellipsis and anaphora resolution.
This annotation style is called tectogrammatical annotation and it constitutes the tectogrammatical layer in the corpus. For more details see below and documentation.
Annotation of the Czech part
Sentences of the Czech translation were automatically morphologically annotated and parsed into surface-syntax dependency trees in the PDT 2.0 annotation style. This annotation style is sometimes called analytical annotation; it constitutes the analytical layer of the corpus. The manual tectogrammatical (deep-syntax) annotation was built as a separate layer above the automatic analytical (surface-syntax) parse. A sample of 2,000 sentences was manually annotated on the analytical layer.
Annotation of the English part
The resulting manual tectogrammatical annotation was built above an automatic transformation of the original phrase-structure annotation of the Penn Treebank into surface dependency (analytical) representations, using the following additional linguistic information from other sources:
PropBank (LDC2004T14)
VerbNet
NomBank (LDC2008T23)
flat noun phrase structures (by courtesy of D. Vadas and J.R. Curran)
For each sentence, the original Penn Treebank phrase structure trees are preserved in this corpus together with their links to the analytical and tectogrammatical annotation. and Ministry of Education of the Czech Republic projects No.:
MSM0021620838
LC536
ME09008
LM2010013
7E09003+7E11051
7E11041
Czech Science Foundation, grants No.:
GAP406/10/0875
GPP406/10/P193
GA405/09/0729
Research funds of the Faculty of Mathematics and Physics, Charles University, Czech Republic, Grant Agency of the Academy of Sciences of the Czech Republic: No. 1ET101120503
Students participating in this project have been running their own student grants from the Grant Agency of the Charles University, which were connected to this project. Only ongoing projects are mentioned: 116310, 158010, 3537/2011
Also, this work was funded in part by the following projects sponsored by the European Commission:
Companions, No. 034434
EuroMatrix, No. 034291
EuroMatrixPlus, No. 231720
Faust, No. 247762
A richly annotated and genre-diversified language resource, The Prague Dependency Treebank – Consolidated 1.0 (PDT-C 1.0, or PDT-C in short in the sequel) is a consolidated release of the existing PDT-corpora of Czech data, uniformly annotated using the standard PDT scheme. PDT-corpora included in PDT-C: Prague Dependency Treebank (the original PDT contents, written newspaper and journal texts from three genres); Czech part of Prague Czech-English Dependency Treebank (translated financial texts, from English), Prague Dependency Treebank of Spoken Czech (spoken data, including audio and transcripts and multiple speech reconstruction annotation); PDT-Faust (user-generated texts). The difference from the separately published original treebanks can be briefly described as follows: it is published in one package, to allow easier data handling for all the datasets; the data is enhanced with a manual linguistic annotation at the morphological layer and new version of morphological dictionary is enclosed; a common valency lexicon for all four original parts is enclosed. Documentation provides two browsing and editing desktop tools (TrEd and MEd) and the corpus is also available online for searching using PML-TQ.
The Prague Dependency Treebank 2.0 (PDT 2.0) contains a large amount of Czech texts with complex and interlinked morphological (two million words), syntactic (1.5 MW) and complex semantic annotation (0.8 MW); in addition, certain properties of sentence information structure and coreference relations are annotated at the semantic level.
PDT 2.0 is based on the long-standing Praguian linguistic tradition, adapted for the current Computational Linguistics research needs. The corpus itself uses the latest annotation technology. Software tools for corpus search, annotation and language analysis are included. Extensive documentation (in English) is provided as well. and 1ET101120413 (Data a nástroje pro informační systémy) MSM 0021620838 (Moderní metody, struktury a systémy informatiky) 1ET101120503 (Integrace jazykových zdrojů za účelem extrakce informací z přirozených textů) 1P05ME752 (Vícejazyčný valenční a predikátový slovník přirozeného jazyka) LC536 (Centrum komputační lingvistiky)