[Apologies for multiple postings]*
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We are happy to announce that 6 new written corpora, 1 new monolingual
lexicon and 1 new speech resource and 1 new multimodal resource are now
available in our catalogue.
*AnCora Spanish 2.0.0*
<http://catalog.elra.info/en-us/repository/browse/ELRA-W0326/>**
ISLRN: 252-495-813-736-1 <http://www.islrn.org/resources/252-495-813-736-1>
The AnCora Spanish Corpus 2.0.0 is a corpus of 500,000 words annotated
at different levels: Lemma and Part of Speech, Syntactic constituents
and functions, Argument structure and thematic roles, Semantic classes
of the verb, Denotative type of deverbal nouns, Nouns related to WordNet
synsets, Named Entities, Coreference relation.
*AnCora Catalan 2.0.0*
<http://catalog.elra.info/en-us/repository/browse/ELRA-W0327/>ISLRN:
186-654-762-852-8
<http://www.islrn.org/resources/186-654-762-852-8>The AnCora Catalan
Corpus 2.0.0 is a corpus of 500,000 words annotated at different levels:
Lemma and Part of Speech, Syntactic constituents and functions, Argument
structure and thematic roles, Semantic classes of the verb, Denotative
type of deverbal nouns, Nouns related to WordNet synsets, Named
Entities, Coreference relation.
*Bulgarian Treebank Corpus*
<http://catalog.elra.info/en-us/repository/browse/ELRA-W0328/>ISLRN:
761-430-854-533-2
<http://www.islrn.org/resources/761-430-854-533-2>The Bulgarian Treebank
Corpus is composed of 156,149 tokens (11,138 sentences) coming from
three main sources in the domain of Grammar Notebooks (1,391 sentences),
News (6,698 sentences), Other (3,049 sentences). It is available with
syntactical and morphological annotation on a sentence basis in
Universal Dependencies format.
*Bulgarian Event Corpus*
<http://catalog.elra.info/en-us/repository/browse/ELRA-W0329/>ISLRN:
832-960-876-604-2
<http://www.islrn.org/resources/832-960-876-604-2>The Bulgarian Event
Corpus is composed 324,905 tokens appropriate for training Named Entity
Recognition (NER), Named Entity Linking (NEL) and Event Recognition
models for Bulgarian in a multidomain context within Humanities. The
texts are domain related. They include documents from the area of Social
Sciences and Humanities – scientific papers, archive documents, popular
documents, and Wikipedia articles in the relevant areas.
*Bulgarian Valency Frame Lexicon*
<http://catalog.elra.info/en-us/repository/browse/ELRA-L0132/>ISLRN:
188-702-981-369-5
<http://www.islrn.org/resources/188-702-981-369-5>The Bulgarian Valency
Frame Lexicon is composed of 9547 lexical entries organized by frames
with 960 mappings to Princeton WordNet available in XML format. It is a
treebank-driven resource of extracted valency frames from BulTreeBank.
The frames were manually curated. The structure of the frames follows
the BulTreeBank syntactic structure.
*How2Sign Dataset*
<http://catalog.elra.info/en-us/repository/browse/ELRA-S0416/>ISLRN:
583-408-694-292-6
<http://www.islrn.org/resources/583-408-694-292-6>The How2Sign dataset
consists of a parallel corpus of speech and transcriptions of
instructional videos and their corresponding American Sign Language
(ASL) translation videos and annotations. It has been produced by
recording 11 persons (6 males and 5 females) with various hearing status
(5 self-identified as hearing, 4 as deaf, 2 as hard of hearing). The
video has been recorded at 30 fps in MPEG format. A total of 80 hours of
Multiview American Sign Language videos were collected, as well as gloss
annotations and a coarse video categorization.
*Persian Speech Corpus*
<http://catalog.elra.info/en-us/repository/browse/ELRA-S0415/>ISLRN:
058-406-130-314-1
<https://islrn.org/resources/058-406-130-314-1/>This dataset contains
more than 31 hours and 30 minutes of Persian scripted monologue and
dialogue data, recorded from 89 Persian speakers (39 males and 50
females) between 17-80 years old in Iran (Tehrani dialect). Data
consists of read and spontaneous speech recordings: books read by a
person, recorded podcasts, articles in the newspapers, radio
conversations, phone dialogues. Domains are labelled and include:include
Accounting, Banking, Economics, Finance, Insurance, Literature,
Marketing, Medicine, Psychology, Science, Technology, Telecommunication,
and Law.
*Venice Italian Treebank (VIT) – version 2*
<http://catalog.elra.info/en-us/repository/browse/ELRA-W0324/>ISLRN:
942-234-530-020-7
<http://www.islrn.org/resources/942-234-530-020-7>This is a new release
of the Venice Italian Treebank (VIT). It consists of the Written and
Spoken VIT subsets. The PennTreebank version of the treebank is also
made available on both subsets using parentheses and also a slightly
modified version using brackets that allows web basedweb-based
visualization tools to build a tree of the structure. The Written VIT
consists of 223,292 tokens excluding punctuation, but 280,641 single
tokens including enclitics and punctuation. It contains a totally
revised constituency basedconstituency-based representation of the
corpus as well as three new files. As for the Spoken VIT, 425 new fully
parsed turns were added for a total of 3973. The total count of
sentences is now 5851.
*Wojood - A corpus for nested Arabic Named Entity Recognition*
<http://catalog.elra.info/en-us/repository/browse/ELRA-W0325/>ISLRN:
688-718-284-176-0
<https://islrn.org/resources/688-718-284-176-0/>Wojood consists of about
550,000 tokens (Modern Standard Arabic and dialect) that are manually
annotated with 21 entity types (person, group of people, occupation,
organization, geopolitical entity, location, facility, event, date,
time, language, website, law, product, cardinal number, ordinal number,
percent, quantity, unit, money, currency). It covers multiple domains
(Media, History, Culture, Health, Finance, ICT, Law, Elections,
Politics, Migration, Terrorism, social media) and was annotated with
nested entities. The corpus contains about 75K entities and 22.5% of
which are nested. The corpus was annotated using the IOB2 tagging scheme
and is available in CSV format.
For more information on the catalogue or if you would like to enquire
about having your resources distributed by ELRA, please *contact us*
<mailto:[email protected]>.
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