Subject-Predicate-Object (SPO) Triple

A Subject-Predicate-Object (SPO) Triple is a 3-tuple that represent Subject (Grammar) and Object (Grammar) and the Predicate (Grammar) that relates them.

• Example(s):
  • Steve Jobs type entrepreneur.
  • entrepreneur subtypeOf businessperson.
  • Steve Jobs coFounded Apple.
  • Steve Jobs hasFriend Steve Wozniak.
  • Steve Jobs hasDaughter Lisa Brennan.
  • Apple Lisa namedAfter Lisa Brennan.
  • Steve Jobs diedOf Pancreatic Cancer.
  • Steve Jobs fanOf Bob Dylan.
• See: Triplestore, Knowledge Representation and Reasoning, Uniform Resource Identifier, Semantic Query, Semantic Reasoner, Entity–Attribute–Value Model, Semantic Network.

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References

2020

• (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/Semantic_triple#Subject,_predicate_and_object Retrieved:2020-5-19.
  • This format enables knowledge to be represented in a machine-readable way. Particularly, every part of an RDF triple is individually addressable via unique URIs — for example, the second statement above might be represented in RDF as:

    http://example.name#BobSmith12 http://xmlns.com/foaf/0.1/knows http://example.name#JohnDoe34.

    Given this precise representation, semantic data can be unambiguously queried and reasoned about.

    The components of a triple, such as the statement "The sky has the color blue", consist of a subject ("the sky"), a predicate ("has the color"), and an object ("blue"). This is similar to the classical notation of an entity–attribute–value model within object-oriented design, where this example would be expressed as an entity (sky), an attribute (color) and a value (blue).

    From this basic structure, triples can be composed into more complex models, by using triples as objects or subjects of other triples — for example, Mike → said → (triples → can be → objects).

    Given their particular, consistent structure, a collection of triples is often stored in purpose-built databases called Triplestores. ...

    ...

2020

• (Tresp et al., 2020) ⇒ Volker Tresp, Sahand Sharifzadeh, Dario Konopatzki, and Yunpu Ma. (2020). “The Tensor Brain: Semantic Decoding for Perception and Memory.” In: arXiv preprint arXiv:2001.11027.
  • QUOTE: ... We analyse perception and memory, using mathematical models for knowledge graphs and tensors, to gain insights into the corresponding functionalities of the human mind. Our discussion is based on the concept of propositional sentences consisting of $\textit{subject-predicate-object}$ (SPO) triples for expressing elementary facts. SPO sentences are the basis for most natural languages but might also be important for explicit perception and declarative memories, as well as intra-brain communication and the ability to argue and reason. A set of SPO sentences can be described as a knowledge graph, which can be transformed into an adjacency tensor. ...

2016

• (Weikum et al., 2016) ⇒ Gerhard Weikum, Johannes Hoffart, and Fabian M. Suchanek. (2016). “Ten Years of Knowledge Harvesting: Lessons and Challenges.” In: IEEE Data Engineering Bulletin, 39(3).
  • QUOTE: ... The largest of the KB’s from these projects contain many millions of entities (i.e., people, places, products etc.) and billions of facts about them (i.e., attribute values and relationships with other entities). Moreover, entities are organized into a taxonomy of semantic classes, sometimes with hundred thousands of fine-grained types. All this is often represented in the form of subject-predicate-object (SPO) triples, following the RDF data model, and some of the KB’s – most notably DBpedia – are central to the Web of Linked Open Data [19]. For illustration, here are some examples of SPO triples about Steve Jobs:
    • Steve Jobs type entrepreneur.
    • entrepreneur subtypeOf businessperson.
    • Steve Jobs coFounded Apple.
    • Steve Jobs hasFriend Steve Wozniak.
    • Steve Jobs hasDaughter Lisa Brennan.
    • Apple Lisa namedAfter Lisa Brennan.
    • Steve Jobs diedOf Pancreatic Cancer.
    • Steve Jobs fanOf Bob Dylan.
  • The most obvious use case for this kind of encyclopedic knowledge is to support search engines (for both Internet and enterprise search) on queries about entities.

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