Quepy
Quepy – a python framework to transform natural language questions to queries in a database query language, can be easily customized to different kinds of questions in natural language and database queries.
Quepy – a python framework to transform natural language questions to queries in a database query language, can be easily customized to different kinds of questions in natural language and database queries.
Yahoo! Content Analysis API – detects entities/concepts, categories, and relationships within unstructured content. It ranks those detected entities/concepts by their overall relevance, resolves those if possible into Wikipedia pages, and annotates tags with relevant meta-data.
dataTXT semantic text API – dataTXT is a set of semantic APIs to extract meaning and insights from texts in several languages. It's optimized for short texts, such as tweets and other social media. dataTXT extracts entities (such as persons, places and events), categorizes documents in user-defined categories, augments the text with tags and links to external knowledge graphs and more.
Cicero On-Demand API (replaced Extractiv) – provides a RESTful interface that wraps LCC's CiceroLite and other NLP components.
AlchemyAPI – cloud-based text mining platform provides semantic tagging through a set of natural language processing capabilities including named entity extraction, sentiment analysis, concept tagging, author extraction, relations extraction, web page cleaning, language detection, keyword extraction, quotations extraction, intent mining, and topic categorization.
DBpedia Spotlight – tool for annotating mentions of DBpedia resources in natural language text, providing capabilities useful for Named Entity Recognition, Name Resolution, amongst other information extraction tasks.
Entityclassifier.eu – a NER tool for annotating entities in free English, German and Dutch texts. It provides entity spotting, disambiguation, classification and linking with DBpedia and YAGO2S resources. The recent version also assigns entity salience information – the level of importance of each entity to the text.