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In this paper, we propose a new framework to annotating subtitled YouTube EDU media fragments using textual features such as exert all the basic portions extracted from the web-based natural language processors of in relation to subtitles and temporal features such as duration of the media fragments where proper entities are spotted. We've created the SY-E-MFSE (Subtitled YouTube EDU Media Fragment Search Engine) as a framework to cruising on the subtitled YouTube EDU videos resident in the Linked Open Data (LOD) cloud. For realizing this purpose, we propose Unifier Module of Outcomes of Web-Based Natural Language Processors (UM-OWNLP) for extracting the essential portions of the 10 NLP tools that are based on the web, from subtitles associated to YouTube videos in order to generate media fragments annotated with resources from the LOD cloud. Then, we propone Unifier Module of Outcomes of WebBased Named Entity (NE) Booster Processors (UM-OWNEBP) containing the six web Application Programming Interfaces (API) to boost outcomes of NEs obtained from UM-OWNLP. We've presented 'UM-OWNLP ontology' to support all the 10 NLP web-based tools ontological features and representing them in a steadfast framework. KeywordsSubtitled YouTube EDU video, textual metadata, semantic web, video annotation, web-based natural language processor.

Named Entity Recognition is a main task in the NLP area that has yielded multiple web-based natural language processors gaining popularity in the Semantic Web community for extracting knowledge from web data. These processors are generally located as pipelines, using dedicated APIs and various taxonomy for extracting, classifying and disambiguating named entities. In this paper, we address the problem of NER on Farsi language by proposing NER-FL, a novel semantic framework which unifies three popular named entity extractors available on the web, and the NER-FL ontology which provides a rich set of axioms aligning the taxonomies of these web natural language processors automatically on the LOD-cloud. KEYWORDSWeb-based natural language processor, named entity, semantic web, ontology, Farsi language

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