a data.frame (or a tibble tbl_df), whose defaultdocument id is a variable identified by docid_field; the text of thedocument is a variable identified by text_field; and other variablesare imported as document-level meta-data. This matches the format ofdata.frames constructed by the the readtext package.
Names to be assigned to the texts. Defaults to the names ofthe character vector (if any); doc_id for a data.frame; the documentnames in a tm corpus; or a vector of user-supplied labels equal inlength to the number of documents. If none of these are round, then"text1", "text2", etc. are assigned automatically.
optional column index of a document identifier; defaultsto "doc_id", but if this is not found, then will use the rownames of thedata.frame; if the rownames are not set, it will use the default sequencebased on ([quanteda_options]("base_docname").
the character name or numeric index of the sourcedata.frame indicating the variable to be read in as text, which mustbe a character vector. All other variables in the data.frame will beimported as docvars. This argument is only used for data.frameobjects.
logical; if TRUE, split each kwic row into two"documents", one for "pre" and one for "post", with this designation savedin a new docvar context and with the new number of documentstherefore being twice the number of rows in the kwic.
For quanteda >= 2.0, this is a specially classed character vector. Ithas many additional attributes but you should not access theseattributes directly, especially if you are another package author. Use theextractor and replacement functions instead, or else your code is not onlygoing to be uglier, but also likely to break should the internal structureof a corpus object change. Using the accessor and replacement functionsensures that future code to manipulate corpus objects will continue to work.
All documents are organized into folders by language, publication year, and publication symbol. Corresponding documents are placed in parallel folder structures, and a document's translation into any of the official languages (if it exists) can be found by inspecting the same file path in the required language subfolder.
For individual documents, it was decided to follow the TEI-based format of the JRC-Acquis parallel corpus. Documents retain the original paragraph structure, and sentence splits have been added automatically. Documents for which multiple language versions exist have corresponding linked files for each of the language pairs, of which there are 15 at most.
In addition to the one-file-per-document type of distribution, we also make available plain-text bi-texts that span all documents for a specific language pair and can be used more readily with SMT training pipelines.
Symbol Each United Nations document has a unique symbol. All language versions of a document have the same symbol. Symbols include both letters and numbers. Some elements of the symbol have meaning, while others do not. In general, the symbol does not necessarily indicate the topic of the document. Translation job number This is a unique, language-specific document identifier. Publication date This is the original publication date for a document by symbol, which applies to all language versions. This date does not necessarily correspond to the release date of each individual document. Processing place Possible locations are New York, Geneva and Vienna. Keywords These include any number of subjects covered by the document, according to the ODS subject lexicon, which is based on the United Nations Bibliographic Information System Thesaurus.
The OpenCitations Corpus (OCC) is an open repository of scholarly citation data made available under a Creative Commons public domain dedication (CC0), which provides accurate bibliographic references harvested from the scholarly literature that others may freely build upon, enhance and reuse for any purpose, without restriction under copyright or database law. An in-depth description of the OCC is available in the following paper:
The corpus URL ( ) identifies the entire OCC, which is composed of several sub-datasets, one for each of the aforementioned bibliographic entities included in the corpus. Each of these has a URL composed by suffixing the corpus URL with the two-letter short name for the class of entity (e.g. be for a bibliographic reference) followed by an oblique slash (e.g. ). Individual members of each sub-dataset are identified by incrementing numbers, unique within that sub-dataset, e.g. or
The ingestion of citation data into the OCC, briefly summarised in Figure 1, is handled by two Python scripts called the bibliographic references Extractor (BEE) and the SPAR Citation Indexer (SPACIN), available in the OpenCitations GitHub repository.
In particular, for each article retrieved by means of the Europe PubMed Central API, BEE stores all the possible identifiers (in the example, doi, pmid, pmcid, and localid) and all the textual references, enriched by their own related identifiers if these are available. In addition, the JSON file also includes provenance information about the source, its provider and the curator (i.e. the particular BEE Python class responsible for the extraction of these metadata from the source).
Starting from the output provided by BEE, SPACIN processes each JSON file, retrieving metadata information about all the citing/cited articles described in it by querying the Crossref API and the ORCID API. These APIs are also used to disambiguate bibliographic resources and agents by means of the identifiers retrieved (e.g., DOI, ISSN, ISBN, ORCID, URL, and Crossref Member URL). Once SPACIN has retrieved all these metadata, appropriate RDF resources are created (or reused, if they have been already added to the OCC in the past). These are stored in the file system in JSON-LD format and additionally within the OCC triplestore. It is worth noting that, for space and performance reasons, the triplestore includes all the data about the curated entities, but does not store their provenance data nor the descriptions of the datasets themselves, which are accessible only via HTTP.
The SPACIN workflow introduced in Figure 1 is a process that runs until no more JSON files are available from BEE. Thus, the current instance of the OCC is evolving dynamically in time (even if now it has been stopped for updating the ingestion scripts), and can be easily extended beyond ingest from Europe PubMed Central by reconfiguring it to interact with additional REST APIs provided by different bibliographic sources, so as to gather new article metadata and their related references, thereby expanding the scope and coverage provided by the OCC.
In each round, he received the maximum allowable point total of 14. He was one of five 8th grade Champions and his score qualifies him to compete in the National Championship in Chicago, taking place over Memorial Day weekend.
Get started by going to our school website at corpuschristiacad.org and filling out an admissions interest form. You can also call our school office at 440-449-4244 for information.
We offer 1:1 technology with every student being issued a device to use during school hours that includes Chromebooks, touch screen Chomebooks, and Ipads. Every classroom is equipped with a classroom laptop, Ipad, and Interactive Whiteboard.
Technology is used seamlessly throughout the school day for everything from education in the arts, math practice, to writing and revising essays. Students are able to interact with the outside world, and put their learning into practice for real world application.
The corpus callosum (plural: corpora callosa) is the largest of the commissural fibers, linking the cerebral cortex of the left and right cerebral hemispheres. It is the largest white matter tract in the brain.
Immediately above the body of the corpus callosum, lies the interhemispheric fissure in which runs the falx cerebri and branches of the anterior cerebral vessels. The superior surface of the corpus callosum is covered by a thin layer of grey matter known as the indusium griseum.
The corpus callosum has a rich blood supply, relatively constant and is uncommonly involved by infarcts. The majority of the corpus callosum is supplied by the pericallosal arteries (the small branches and accompanying veins forming the pericallosal moustache) and the posterior pericallosal arteries, branches from the anterior and posterior cerebral respectively. In 80% of patients, additional supply comes from the anterior communicating artery, via either the subcallosal artery or median callosal artery.
subcallosal artery (50% of patients) is essentially a large version of a hypothalamic branch, which in addition to supplying part of the hypothalamus also supplies the medial portions of the rostrum and genu
median callosal artery (30% of patients) can be thought of as a more extended version of the subcallosal artery, in that it travels along the same course, supplies the same structures but additionally reaches the body of the corpus callosum
Various small veins draining the central parts of the corpus callosum drain into the internal cerebral veins, in turn draining into the straight sinus. Tributaries of the internal cerebral veins draining the corpus callosum include 10:
Studies, including using MR tractography, cast some doubt on this assertion, instead suggesting that the anterior body develops first and then continues bidirectionally, with the anterior portions (genu) developing earlier/more prominently than the posterior portions (splenium) 7,8. This is not, however, universally accepted 11.
These rules have been adopted to provide the procedure for post-conviction habeas corpus proceedings as they are set forth in West Virginia Code 53-4A-1 et seq. These rules supplement, and in designated instances supersede, the statutory procedures set forth in 53-4A-1 et seq. of the West Virginia Code. For petitions filed in any circuit court in the State, all of the rules apply. For petitions filed in the Supreme Court of Appeals, only Rule 2 applies.
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