Posted:January 25, 2017

CognontoEight Cognonto Use Cases are Now Available

Since its initial release in September, we have continued to refine Cognonto’s KBpedia knowledge structure that integrates six major knowledge bases (Wikipedia, Wikidata, OpenCyc, GeoNames, DBpedia and UMBEL), plus mappings to another 20 leading ones. KBpedia provides a foundation for knowledge-based artificial intelligence (KBAI) by supporting the (nearly) automatic creation of training corpuses and positive and negative training sets and feature sets for deep, unsupervised and supervised machine learning.

Our most recent efforts have been to expand the scope and completeness of KBpedia, largely based on filling gaps in the current structure using local Wikipedia categories. This ongoing effort is making sure that the overall KBpedia structure represents the best amalgam of structure and content from KBpedia’s contributing knowledge bases. There should be an announcement of a new KBpedia release arising from these current efforts soon.

However, in the process of enhancing the Cognonto Mapper for this expansion, two new use cases have resulted from our efforts. The first use case outlines how we have used the DeepWalk graph embedding model to expand KBpedia using Wikipedia category information. The second use case, again using DeepWalk, is a fast method for accurate concept disambiguation.

With these two additions, Cognonto now has eight diverse use cases:

Each use case is summarized according to the problem and our approach to solving it and the benefits that result. The use cases themselves present general workflows and code snippets for how the use case was tackled.

We will continue to publish use cases using Cognonto’s technologies and KBpedia as they arise. Also, stay tuned for the expanded KBpedia release.

Posted:December 12, 2016

Recent Slideshow Posted on KBpedia

Last week I gave a presentation to the Ontolog Forum on Cognonto, with specific reference to the KBpedia knowledge structure. I am pleased to now post this presentation online:

As a standard method, the Forum routinely records the audio of its presentations. So, if you desire, you can listen to my 60 min presentation (followed by a 30 min Q & A) by clicking this audio link. The slide numbers are noted as the audio presentation proceeds so you can synchronize the audio with the slides.

We’re very pleased to have been giving this opportunity by the Forum. We invite you to hear this introduction to Cognonto and KBpedia.

Posted:December 5, 2016

CognontoPart of Our Ongoing Efforts to Better Represent Knowledge

Cognonto today announced the release of version 1.20 of KBpedia, its knowledge structure that integrates six major knowledge bases (Wikipedia, Wikidata, OpenCyc, GeoNames, DBpedia and UMBEL) and 20 subsidiary ones under the KBpedia Knowledge Ontology (KKO). KBpedia’s explicit purpose is to provide a foundation for knowledge-based artificial intelligence (KBAI) by supporting the (nearly) automatic creation of training corpuses and positive and negative training sets and feature sets for deep, unsupervised and supervised machine learning.

The changes in this new release are solely related to KKO, the knowledge graph portion of KBpedia. There are two major drivers for this update to the KBpedia upper ontology. First, internal development efforts are now focusing on the modeling of predicates and time and action. This effort affects the definitions, splits and boundaries between attributes, relations, events and activities. Revisions in this area have been derived from a much closer reading of Charles Sanders Peirce‘s writings, based on our view that CSP has the most logical and sophisticated understanding of knowledge representation yet expressed. Second, where appropriate, we have relied on Peircean terminology to capture specific concepts. We are doing this to make KKO more amenable to review by Peircean scholars. At the same time, we have tried to reduce the use of obscure or difficult Peircean terms where they might be a barrier to understanding.

These changes solely affect two of the three main branches in KKO. The most affected branch is Monads, the branch representing Firstness (see below), reflecting the basic concepts or building blocks used in KKO. The Particulars branch, which captures the representation of individuals or instances, also was modified to capture those changes in the Monads branch. The Generals branch, the main portion for classes and types, was not affected by these changes.

The resulting KKO upper structure now has this form with about 165 key concepts, all organized according to Peirce’s universal categories of Firstness (1ns), Secondness (2ns) and Thirdness (3ns) (I earlier provided a broad overview for the basis of this triadic design):

level 1 level 2 level 3 level 4 level 5 level 6 level 7
Monads [1ns]
FirstMonads [1ns]
Suchness [1ns]
Accidental [1ns]
Inherent [2ns]
Relational [3ns]
Thisness [2ns]
Chance [1ns]
Being [2ns]
Form [3ns]
Pluralness [3ns]
Absolute [1ns]
Inclusive [1ns]
Exclusive [2ns]
Difference [3ns]
SimpleRelative [2ns]
Conjugative [3ns]
DyadicMonads [2ns]
Attributives [1ns]
Oneness [1ns]
Identity [1ns]
Real [2ns]
Matter [1ns]
SubstantialForm [2ns]
AccidentalForm [3ns]
Fictional [3ns]
Otherness [2ns]
Inherence [3ns]
Quality [1ns]
Negation [2ns]
Intrinsic [3ns]
Relatives [2ns]
Concurrents [1ns]
Opponents [2ns]
Conjunctives [3ns]
Quantity [1ns]
Values [1ns]
Numbers [1ns]
Multitudes [2ns]
Magnitudes [3ns]
Discrete [2ns]
Continuous [3ns]
Subsumption [2ns]
Connective [3ns]
Unary [1ns]
Binary [2ns]
Conditional [3ns]
Indicatives [3ns]
Iconic [1ns]
Indexical [2ns]
Associative [3ns]
Denotative [1ns]
Similarity [2ns]
Contiguity [3ns]
TriadicMonads [3ns]
Representation [1ns]
Icon [1ns]
Index [2ns]
Symbol [3ns]
Mediation [2ns]
Mentation [3ns]
Particulars [2ns]
MonadicDyads [1ns]
MonoidalDyad [1ns]
EssentialDyad [2ns]
InherentialDyad [3ns]
Events {2ns]
Action [1ns]
Change [1ns]
Exertion [2ns]
Perception [3ns]
Reaction [2ns]
State [1ns]
Volition [2ns]
Thought [3ns]
Continuous [3ns]
Space [1ns]
Points [1ns]
Areas [2ns]
2D Dimensions
SpaceRegions [3ns]
3D Dimensions
Time [2ns]
Instants [1ns]
Intervals [2ns]
Eternal [3ns]
Duratives [3ns]
Situations [1ns]
Activities [2ns]
Processes [3ns]
Entities [3ns]
SingleEntities [1ns]
Phenomenal [1ns]
Ideal [2ns]
Conceptual [3ns]
PartOfEntities [2ns]
Members [1ns]
Parts [2ns]
FunctionalComponents [3ns]
ComplexEntities [3ns]
CollectiveStuff [1ns]
MixedStuff [2ns]
CompoundEntities [3ns]
Generals [3ns] (== SuperTypes)
SignElements [1ns]
AttributeTypes [1ns]
RelationTypes [2ns]
SituationTypes
Symbols [3ns]
Primitives [1ns]
Structures [2ns]
Conventions [3ns]
Constituents [2ns]
NaturalPhenomena [1ns]
SpaceTypes [2ns]
Shapes [1ns]
Places [2ns]
LocationPlace
AreaRegion
Forms [3ns]
TimeTypes [3ns]
Times [1ns]
EventTypes [2ns]
ActivityTypes [3ns]
Manifestations [3ns]
NaturalMatter [1ns]
AtomsElements [1ns]
NaturalSubstances [2ns]
Chemistry [3ns]
OrganicMatter [2ns]
OrganicChemistry [1ns]
BiologicalProcesses
LivingThings [2ns]
Prokaryotes [1ns]
Eukaryotes [2ns]
ProtistsFungus [1ns]
Plants [2ns]
Animals [3ns]
Diseases [3ns]
Agents [3ns]
Persons [1ns]
Organizations [2ns]
Geopolitical [3ns]
Symbolic [3ns]
Information [1ns]
AVInfo [1ns]
VisualInfo
AudioInfo
WrittenInfo [2ns]
StructuredInfo [3ns]
Artifacts [2ns]
FoodDrink
Drugs
Products
Facilities
Systems [3ns]
MentalProcesses [1ns]
Concepts [1ns]
TopicsCategories [2ns]
LearningProcesses [3ns]
SocialProcesses [2ns]
FinanceEconomy
Society
Science [3ns]

It is useful to re-cap the three constituents of Peirce’s trichotomy, what he called simply the Three Categories, or the universal categories, as follows:

  • Firstness [1ns] — these are possibilities or potentials, the basic forces or qualities that combine together or interact in various ways to enable the real things we perceive in the world, such as matter, life and ideas. These are the unrealized building blocks, or elements, the essences or attributes or possible juxtapositions. They are not divisible, what Peirce called indecomposables, since they are integral qualities or ideas in themselves;
  • Secondness [2ns] — these are the particular realized things or concepts in the world, what we can perceive, point to and describe. A particular is also known as an event, entity, instance or individual; and
  • Thirdness [3ns] — these are the laws, habits, regularities and continuities that may be generalized from particulars. All generals — what are also known as classes, kinds or types — belong to this category. The process of finding and deriving these generalities also leads to new insights or emergent properties, which continue to fuel knowledge discovery. Insights arising from Thirdness enable us to further explore and understand things, and is a driving force for further categorization.

Note that the three main branches and most of the sub-branches to KKO conform to this triadic structure. The basis for this structure was discussed in an earlier article.

In future posts I will delve and explain further each of the main branches of KKO. It is also likely the changes and refinements to this upper structure may continue for some time. Cognonto has open sourced KKO both for use by others and as a means for Peircean scholars and students to make critical commentary and suggestions. Because of this desire for review, we have also annotated the KKO structure more extensively in this release, including references to specific passages from Peirce’s writings.

Remember, KBpedia and KKO are the first complete attempt to capture Charles S. Peirce’s views of the logical organization of knowledge and the theory of signs into a working computer ontology (knowledge graph). As with Peirce’s views of ‘truth‘ as a limit function that can be approached but never fully attained, we will continue to strive to improve our understanding of how best to model knowledge for artificial intelligence purposes. The good news is we are already realizing significant KBAI benefits from KBpedia in its current form. We expect those benefits to continue to grow with further refinements to KKO and its typologies.

The open source KBpedia Knowledge Ontology (KKO) may be downloaded and inspected from here. We welcome any and all critical commentary.

Posted:December 1, 2016

CognontoPublic Ontolog Forum Talk to Emphasize KBpedia

The Ontolog Forum, the online community of practice for ontologists, has just announced a public online meeting on Cognonto. I will be giving the roughly 60 min presentation, to be followed by 30 min of open discussion, on December 7 at 9:30am Pacific / 12:30pm Eastern / 6:30pm CEST / 5:30pm GMT / 1730 UTC.  The public is invited.

According to the announcement:

KBpedia is a recently announced knowledge structure that integrates six major knowledge bases (OpenCyc, Wikipedia, Wikidata, GeoNames, DBpedia, UMBEL) under the KBpedia Knowledge Ontology (KKO). KBpedia’s explicit purpose is to provide a foundation for knowledge-based artificial intelligence by supporting the (nearly) automatic creation of training corpuses and positive and negative training sets and feature sets for deep, unsupervised and supervised machine learning. KKO is the upper ontology for KBpedia, and is guided by the universal categories (Firstness, Secondness, Thirdness) of Charles S. Peirce. [This talk] will discuss what KBpedia is, how it is organized and constructed, and why KKO offers some new approaches to vexing metaphysical questions in ontology design related to the knowledge representation of entities, relations, attributes, concepts, and natural kinds. The discussion period will hopefully highlight next potentials and important open questions.

Instructions and dial-in numbers are provided on the meeting announcement site. Please note that Ontolog has an open intellectual property rights policy.

I hope to see you there!

Posted:November 28, 2016

Dataversity has just published an article on Cognonto based on an interview of me and review of our online materials. The article, Cognonto Takes On Knowledge-Based Artificial Intelligence,” does an excellent job of summarizing the venture. The writer, Jennifer Zaino, did a fantastic job capturing our discussions and framing the Cognonto story. Thanks!

I especially like that the article begins with the simple words, knowledge-based artificial intelligence, which is the quintessential description of what Cognonto is about. Jennifer then goes on to explain the genesis of the venture, the central role of its knowledge structure KBpedia, and the basis of this knowledge graph grounded in the triadic logic of the 19th century philosopher, Charles Sanders Peirce.

We will use this article for months to come in helping others understand what we are doing and why. It is always refreshing to see intelligent, well-written journalism. Thanks, Jenny.