Figure1-Data, information, knowledge: conceptual differences

to assess its level of confidence in responses to user queries.

“Semantics without the ability to connect to other data is almost as valueless as no semantics…[S]emantic data [is] only valuable in my opinion when it can be bridged to other data.”

Thanks to Schema.org’s vocabulary, strings of text could be understood as things containing unique properties and relationships with other things on the web.

As Google themselves stated: “At its core, Search is about understanding language.” Following this statement, it only makes sense that the biggest challenge facing SEO today is one of semantics. At its most basic, semantics is a term for the study of language, how it expresses meaning, and the rules it must abide by in order to convey this meaning. It comes as no surprise that semantics have had a significant impact on search function and SEO strategy.

the performance of generation is still far fromsatisfaction in many real-world scenarios. For example, in dialogue systems, conditioning on only theinput text, a text generation system often produces trivial or non-committal responses of frequentwords or phrases in the corpus [87,135,148], such as“Me too.”or“Oh my god!”given the inputtext“My skin is so dry.”These mundane responses lack meaningful content, in contrast to humanresponses rich in knowledge. In comparison, humans are constantly acquiring, understanding, andstoring knowledge frombroader sourcesso that they can be employed to understand the currentsituation in communicating, reading, and writing. For example, in conversations, people often firstselectconcepts from related topics(e.g., sports, food), then organize those topics into understandablecontent to respond; for summarization, people tend to write summaries containingkeywordsusedin the input document and perform necessary modifications to ensure grammatical correctness andfluency; in question answering (QA), people usecommonsenseorprofessional knowledgepertainedto the question to infer the answer. Therefore, it is often the case that knowledge beyond the inputsequence is required to produce informative output text.

EventSeries has been defined as a kind of Event to make it easy for publishers to use it in an Event context without worrying about which kinds of series are really event-like enough to call an Event. In general an EventSeries may seem more Event-like when the period of time is compact and when aspects such as location are fixed, but it may also sometimes prove useful to describe a longer-term series as an Event.

Schema Ap