Difference between Semantic Web and NLP?

Question

What exactly is the difference between Semantic Web and Natural Language Processing?

Is Semantic Web a part of Natural Language Processing?

Werby

This question appears to be off-topic because it is purely about terminology, and in a field only indirectly linked to programming. – Silverts

Answer 1

These are two separate subject areas but they do overlap in some places. Because documents, regardless of their format are made up of heterogeneous syntax and semantics, the goal is to represent information that is understandable to a machine and not just a human being. This is a common goal of the Semantic Web and Natural Language Processing.

Semantic Web

The semantic web is based on two fundamental ideas:

• Associating meta-information with Internet-based resources. Metadata is pieces of information about other data which can be added explicitly or implicitly.
• The ability to reason about the meta-information. For example, a machine should be able to recognize that a picture of balloon is not an animal, even if it is shaped like one. This idea of reasoning and inference on textual data is still very experimental, however, showing considerable success. There is a range of techniques to query such information such as SPARQL, Machine Learning (a pre-annotated corpus), and other statistical techniques.

The use of ontologies is becoming evermore important in this domain. Description Logic provides the mathematical foundation for knowledge representation systems and can be used to reason with the information.

Natural Language Processing

Whereas Natural Language Processing is an important and ongoing research area in theoretical computer science and artificial intelligence, it can look beyond the web and process anything from text in PDFs to speaking to your phone. Wikipedia has highlighted some of the key areas which I will expand on:

1. Automatic (Abstractive & Extractive) Summarisation
2. Coreference Resolution
3. Discourse Analysis
4. Language Translation
5. Morphological Segmentation
6. Named Entity Recognition
7. Natural Language Generation
8. Optical Character Recognition
9. Parsing
10. Question Answering
11. Relationship (Semantics) Extraction
12. Speech Segmentation
13. Speech & Voice Recognition
14. Topic Segmentation
15. Word Sense Disambiguation (WSD)
16. Information Retrieval
17. Information Extraction
18. Text Simplification
19. Spelling Correction

Both subject areas have been heavily researched into the syntactics of language, both research fields aim to understand language, notably text. However, in recent times the use of semantics has had a lot of time and investment put into it. But in essence, how to represent relationships in text and miscellaneous structures is a top priority of both fields of thought.

Conclusion

Semantic Web is mostly annotated with RDF, OWL, etc., whereas NLP really focuses on freeform Text.

Alloy

Doesn't the second fundamental idea of semantic web sound more like Machine Learning? – Werby

Reasoning can be practiced in many forms, not just machine learning. The method chosen is nothing more than a means to achieve the goal. @KoushikBalajiVenkatesan :-) – Alloy

Answer 2

Short answer to the second question: no. Semantic web and natural language processing, in computer science, have common topics and there are tools that use both, but neither is part of the other. Semantic web is based on machine understandable languages (RDF, OWL) and related protocols (SPARQL, Linked Data, and so on). Natural language processing works with understanding natural languages, like the text of this answer. See for example GATE for a framework and a lot of research papers in the area.

Boson

Answer 3

These two areas are very different and in a sense complementory to one another. Semantic Web technologies deal with representation, standardization and reasoning about "facts". Important issues include defining vocabularies and designing so called ontologies. Semantic Web technologies do not deal very much with the question where these "facts" come from (at most, data integration comes to mind). Natural Language Processing on the other hand deals with trying to automatically understand the meaning of natural language texts. So this is more of a low-level activity that can serve as input for Semantic Web. The output of NLP is usually not modeled in a sophisticated manner, but comes as "X is an entity", "X relates to Y", etc. Furthermore, NLP does not deliver results that are 100% correct as many of its techniques are based on statistics (neither does Semantic Web, obviously, but I am unaware that questions of precision and especially recall play an important role there).

Amylopectin

I wouldn't say NLP is 'low level' as an activity, it just has a less explicitly structured input. But the explanation of the differences is good in my opinion, not sure why it was downvoted. – Boson

Answer 4

Natural language processing (NLP) and Semantic Web technologies are both Semantic Technologies, but with different and complementary roles in data management. In fact, the merging of NLP and Semantic Web technologies enables people to combine structured and unstructured data in ways that are not viable using traditional tools.

A goal of Semantic Web technologies is to convert unstructured data to meaningful representations, and this can be achieved with the application of NLP technologies. In conclusion, Semantic Web and NLP technologies can enhance each other, for example, Web 3.0. To learn more about Web 3.0 please take a look at the online source What is Web 3.0? Link: https://en.softonic.com/articles/what-is-web-3-0

Overthecounter

Answer 5

They are related technologies. A chatbot for example will use both NLP and Semantic Technologies. I have worked on one.

Schizogenesis

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