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The following commands can be used to invoke them:\n\nThe scripts import data from the `Disease Ontology `_,\n`Wikidata `_\nand `ITIS `_.\nYou should review their licenses and terms of use before using this data.\nCurrently the Disease Ontology is under public domain and ITIS requests citation.\n\n.. code:: bash\n\n python -m epitator.importers.import_species\n # By default entities under the disease by infectious agent class will be\n # imported from the disease ontology, but this can be altered by supplying\n # a --root-uri parameter.\n python -m epitator.importers.import_disease_ontology\n python -m epitator.importers.import_wikidata\n\n\nUsage\n-----\n\n.. code:: python\n\n from epitator.annotator import AnnoDoc\n from epitator.resolved_keyword_annotator import ResolvedKeywordAnnotator\n doc = AnnoDoc(\"5 cases of smallpox\")\n doc.add_tiers(ResolvedKeywordAnnotator())\n annotations = doc.tiers[\"resolved_keywords\"].spans\n annotations[0].metadata[\"resolutions\"]\n # = [{'entity': , 'entity_id': u'http://purl.obolibrary.org/obo/DOID_8736', 'weight': 3}]\n\n\nCount Annotator\n---------------\n\nThe count annotator identifies counts, and case counts in particular.\nThe count's value is extracted and parsed. Attributes such as whether the count\nrefers to cases or deaths, or whether the value is approximate are also extracted.\n\nUsage\n-----\n\n.. code:: python\n\n from epitator.annotator import AnnoDoc\n from epitator.count_annotator import CountAnnotator\n doc = AnnoDoc(\"5 cases of smallpox\")\n doc.add_tiers(CountAnnotator())\n annotations = doc.tiers[\"counts\"].spans\n annotations[0].metadata\n # = {'count': 5, 'text': '5 cases', 'attributes': ['case']}\n\n\nDate Annotator\n--------------\n\nThe date annotator identifies and parses dates and date ranges.\nAll dates are parsed into datetime ranges. For instance, a date like \"11-6-87\"\nwould be parsed as a range from the start of the day to the start of the next day,\nwhile a month like \"December 2011\" would be parsed as a range from the start\nof December 1st to the start of the next month.\n\nUsage\n-----\n\n.. code:: python\n\n from epitator.annotator import AnnoDoc\n from epitator.date_annotator import DateAnnotator\n doc = AnnoDoc(\"From March 5 until April 7 1988\")\n doc.add_tiers(DateAnnotator())\n annotations = doc.tiers[\"dates\"].spans\n annotations[0].metadata[\"datetime_range\"]\n # = [datetime.datetime(1988, 3, 5, 0, 0), datetime.datetime(1988, 4, 7, 0, 0)]\n\n\nStructured Data Annotator\n-------------------------\n\nThe structured data annotator identifies and parses embedded tables.\n\nUsage\n-----\n\n.. code:: python\n\n from epitator.annotator import AnnoDoc\n from epitator.structured_data_annotator import StructuredDataAnnotator\n doc = AnnoDoc(\"\"\"\n species | cases | deaths\n Cattle | 0 | 0\n Dogs | 2 | 1\n \"\"\")\n doc.add_tiers(StructuredDataAnnotator())\n annotations = doc.tiers[\"structured_data\"].spans\n annotations[0].metadata\n # = {'data': [\n # [AnnoSpan(1-8, species), AnnoSpan(11-16, cases), AnnoSpan(19-25, deaths)],\n # [AnnoSpan(26-32, Cattle), AnnoSpan(36-37, 0), AnnoSpan(44-45, 0)],\n # [AnnoSpan(46-50, Dogs), AnnoSpan(56-57, 2), AnnoSpan(64-65, 1)]],\n # 'delimiter': '|',\n # 'type': 'table'}\n\n\nStructured Incident Annotator\n-----------------------------\n\nThe structured incident annotator identifies and parses embedded tables that\ndescribe case counts paired with location, date, disease and species metadata.\nMetadata is also extracted from the text around the table.\n\nUsage\n-----\n\n.. code:: python\n\n from epitator.annotator import AnnoDoc\n from epitator.structured_incident_annotator import StructuredIncidentAnnotator\n doc = AnnoDoc(\"\"\"\n Fictional October 2015 rabies cases in Svalbard\n \n species | cases | deaths\n Cattle | 0 | 0\n Dogs | 4 | 1\n \"\"\")\n doc.add_tiers(StructuredIncidentAnnotator())\n annotations = doc.tiers[\"structured_incidents\"].spans\n annotations[-1].metadata\n # = {'location': {'name': u'Svalbard', ...},\n # 'species': {'label': u'Canidae', ...},\n # 'attributes': [],\n # 'dateRange': [datetime.datetime(2015, 10, 1, 0, 0), datetime.datetime(2015, 11, 1, 0, 0)],\n # 'type': 'deathCount',\n # 'value': 1,\n # 'resolvedDisease': {'label': u'rabies', ...}}\n\n\nArchitecture\n============\n\nEpiTator provides the following classes for organizing annotations.\n\nAnnoDoc - The document being annotated. The AnnoDoc links to the tiers of annotations applied to it.\n\nAnnoTier - A group of AnnoSpans. Each annotator creates one or more tiers of annotations.\n\nAnnoSpan - A span of text with an annotation applied to it.\n\nLicense\n=======\n\nCopyright 2016 EcoHealth Alliance\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \"AS IS\" BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License.\n",
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