Information Extraction – Named Entity Recognition Sample Clauses

Information Extraction – Named Entity Recognition. ‌ A particular scenario of information extraction is the recognition of entity references (such as authors, headings, citations, persons, organizations, places, time periods, etc.) and their resolution to real world entities. In this scenario, the entity references are found within unstructured text or in semi-structured data fields. The typical output of this scenario is the exact location of where the entities are mentioned within the data, and their resolution to a set of entities known to be disambiguated – text is enriched with appropriate tags or attributes. Previous research on information extraction has focused mainly on natural lan- guage processing. Information extraction processes are composed of subtasks, each task simplifies the text by transforming it into more machine processable structures. So, for example, before entities can be recognized it may be necessary to identify the language of the text, to tokenize the text into paragraphs, sentences and words, and to classify the words for their part-of-speech category. It is by reasoning on the output of this process that references to entities are identified. This process is therefore dependent on evidence given by the natural language text to identify a reference to an entity, and also its type. Information extraction relies mainly on natural language processing. It consists of a process composed of subtasks that simplify the text by transforming it into more machine processable structures. Some of the typical information extraction subtasks are: Entity recognition: recognition of entity names (persons, organizations, places, temporal expressions, numerical expressions, etc.). Coreference resolution: detection of coreference and anaphoric links between text entit- ies. Word sense disambiguation: identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. Terminology extraction: finding the relevant terms for a given corpus. Relationship extraction: identification of relations between entities (such as person works for organization ). Entity recognition is one of the major subtasks of information extraction. Because of the complexity of the problem, entity recognition is typically studied on restricted domains. The design of an entity resolution system needs to take into considerations the characteristics of the corpus where it is to be applied, such as the languages, textual genres, domains and types of entities. In general terms, any entity re...
Sample 1
AutoNDA by SimpleDocs

Related to Information Extraction – Named Entity Recognition

  • SERVICE MONITORING, ANALYSES AND ORACLE SOFTWARE 11.1 We continuously monitor the Services to facilitate Oracle’s operation of the Services; to help resolve Your service requests; to detect and address threats to the functionality, security, integrity, and availability of the Services as well as any content, data, or applications in the Services; and to detect and address illegal acts or violations of the Acceptable Use Policy. Oracle monitoring tools do not collect or store any of Your Content residing in the Services, except as needed for such purposes. Oracle does not monitor, and does not address issues with, non-Oracle software provided by You or any of Your Users that is stored in, or run on or through, the Services. Information collected by Oracle monitoring tools (excluding Your Content) may also be used to assist in managing Oracle’s product and service portfolio, to help Oracle address deficiencies in its product and service offerings, and for license management purposes.

  • Billing Information 6.1 NLT and the RL shall provide each other with information within their possession that is necessary to allow them to provide accurate and timely billing to each other and to any other relevant third parties.

  • Enterprise Information Management Standards Grantee shall conform to HHS standards for data management as described by the policies of the HHS Office of Data, Analytics, and Performance. These include, but are not limited to, standards for documentation and communication of data models, metadata, and other data definition methods that are required by HHS for ongoing data governance, strategic portfolio analysis, interoperability planning, and valuation of HHS System data assets.

  • Vendor Logo (Supplemental Vendor Information Only) No response Optional. If Vendor desires that their logo be displayed on their public TIPS profile for TIPS and TIPS Member viewing, Vendor may upload that logo at this location. These supplemental documents shall not be considered part of the TIPS Contract. Rather, they are Vendor Supplemental Information for marketing and informational purposes only. Bid Attributes Disadvantaged/Minority/Women Business & Federal HUBZone Some participating public entities are required to seek Disadvantaged/Minority/Women Business & Federal HUBZone ("D/M/WBE/Federal HUBZone") vendors. Does Vendor certify that their entity is a D/M/WBE/Federal HUBZone vendor? If you respond "Yes," you must upload current certification proof in the appropriate "Response Attachments" location. NO Historically Underutilized Business (HUB) Some participating public entities are required to seek Historically Underutilized Business (HUB) vendors as defined by the Texas Comptroller of Public Accounts Statewide HUB Program. Does Vendor certify that their entity is a HUB vendor? If you respond "Yes," you must upload current certification proof in the appropriate "Response Attachments" location. No National Coverage Can the Vendor provide its proposed goods and services to all 50 US States? Yes

  • Certified and Minority Business Enterprises Reports Upon Customer request, the Contractor shall report to the requesting Customer the Contractor’s spend with certified and other minority business enterprises in the provision of commodities or services related to the Customer’s orders. These reports shall include the period covered, the name, minority code, and Federal Employer Identification Number of each minority business utilized during the period; commodities and services provided by the minority business enterprise, and the amount paid to each minority business enterprise on behalf of the Customer.

  • How Do I Get More Information? For more information, including the full Notice, Claim Forms and Settlement Agreement go to xxx.xxxxxxxxxxxxxxxxxxxx.xxx, contact the settlement administrator at 0-000-000-0000, or call Class Counsel at 1-866-354-3015. Exhibit E UNITED STATES DISTRICT COURT FOR THE SOUTHERN DISTRICT OF FLORIDA Xxxxx v. AvMed, Inc., Case No. 10-cv-24513 If You Paid for or Received Insurance from AvMed, Inc. at Any Time Through December of 2009, You May Be Part of a Class Action Settlement. IMPORTANT: PLEASE READ THIS NOTICE CAREFULLY. THIS NOTICE RELATES TO THE PENDENCY OF A CLASS ACTION LAWSUIT AND, IF YOU ARE A MEMBER OF THE SETTLEMENT CLASSES, CONTAINS IMPORTANT INFORMATION ABOUT YOUR RIGHTS TO MAKE A CLAIM UNDER THE SETTLEMENT OR TO OBJECT TO THE SETTLEMENT (A federal court authorized this notice. It is not a solicitation from a lawyer.) Your legal rights are affected whether or not you act. Please read this notice carefully. YOUR LEGAL RIGHTS AND OPTIONS IN THIS SETTLEMENT SUBMIT A CLAIM FORM This is the only way to receive a payment. EXCLUDE YOURSELF You will receive no benefits, but you will retain any rights you currently have to xxx the Defendant about the claims in this case. OBJECT Write to the Court explaining why you don’t like the Settlement. GO TO THE HEARING Ask to speak in Court about your opinion of the Settlement. DO NOTHING You won’t get a share of the Settlement benefits and will give up your rights to xxx the Defendant about the claims in this case. These rights and options – and the deadlines to exercise them – are explained in this Notice. QUESTIONS? CALL 0-000-000-0000 TOLL FREE, OR VISIT XXX.XXXXXXXXXXXXXXXXXXXX.XXX PARA UNA NOTIFICACIÓN EN ESPAÑOL, LLAMAR O VISITAR NUESTRO WEBSITE BASIC INFORMATION

  • CENTURYLINK OSS INFORMATION 57.1 Subject to the provisions of this Agreement and Applicable Law, CLEC shall have a limited, revocable, non-transferable, non-exclusive right to use CenturyLink OSS Information during the term of this Agreement, for CLEC’s internal use for the provision of Telecommunications Services to CLEC End Users in the State.

  • Special Service networks The following services must be received from special service network providers in order to be covered. All terms and conditions outlined in the Summary of Benefits apply.

  • Local Health Integration Networks and Restructuring In the event of a health service integration with another service provider the Employer and the Union agree to meet.

  • Verizon OSS Information 8.5.1 Subject to the provisions of this Section 8, in accordance with, but only to the extent required by, Applicable Law, Verizon grants to CBB a non-exclusive license to use Verizon OSS Information.

Time is Money Join Law Insider Premium to draft better contracts faster.