Context, Perspective, and Generalitiesin a Knowledge Ontology
TM
Ontolog Forum
Michael K. BergmanDecember 7, 2016
© Copyright 2016. Cognonto LLC2
OutlineI. GenesisII. What is KBpedia?III. How is it Constructed?IV. Why it Offers New Ontological ChoicesV. Open Discussion
I. Genesis
TM
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8 Years in Process 2008: UMBEL – reference concepts for Web integration
2008: mapping to Cyc 2009: first typology design (‘SuperTypes’)
2010: mapping to Wikipedia; Wikipedia in KR
2011: my first writings on Charles Sanders Peirce
2011 ff: entity recognition, classification
2013: ‘Aha!’ moment; Cognonto effort begins 2014: re-inspection of UMBEL (Cyc, design, purpose)
2016: first release of Cognonto, KBpedia
© Copyright 2016. Cognonto LLC5
A Growing Fascination with Peirce Charles Sanders Peirce (“purse”) (1839-1914) Polymath, philosopher, scientist,
logician, mathematician John Sowa’s writings Key contributions (much untranscribed):
Logic of semiosis Predicate logic, notations Classification of signs, classification (general) Universal categories (Firstness, Secondness, Thirdness) Pragmaticism (Pragmatic Maxim) Abductive logic Existential graphs
IMO: Greatest thinker on knowledge and KR
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The ‘Aha!’ Moment Inconsistent, incoherent Wikipedia categories Wikipedia bespoke, core knowledge structure in:
DBpedia Freebase Google KG, Now Siri
Big data was a key driver in recent AI breakthroughs 2013: Why not systematize knowledge bases for AI
purposes? KBAI Intuition:
Multiple KBs Shared foundation Fine-grained types (70K +)
IBM Watson Cortana Viv etc.
Need for common schema Design for AI (features,
structure, KR model)
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Exciting Research and Growth Options Nearly automatic creation of training sets and
corpuses Rich structure and feature sets New AI testbed for knowledge representation (KR) Integrating graph models with standard KR, AI Application of abductive logic to learning processes More powerful basis for data interoperability,
integration
II. What is KBpedia?
TM
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Cognonto Overview Cognonto = cognition + ontology = knowledge-based AI (KBAI) Boutique enterprise services:
Supervised, unsupervised, deep machine learning Information integration Recognition, extraction, tagging Specialty expertise
Three technology components KBpedia: integration of 6 + 20 KBs Developing use cases with clients
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KBpedia Knowledge Structure
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20 Other KBs, Vocabularies Bibliography Ontology Creative Commons DBpedia Ontology Description of a Project
(DOAP) Dublin Core Event Ontology FRBR Friend of a Friend Geo
Music Ontology Open Organizations Organization Ontology Programmes Ontology RSS Ontology schema.org SIOC Time Ontology TRANSIT US PTO
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KBpedia Design Basis Based on triadic logic of C.S. Peirce Feature-rich KKO structure:
Entities Attributes Relations Events
Written in OWL2: Reasoning Inference SPARQL
Explicitly structured for AI in: Natural language understanding (NLU) Feature extraction and generation Labeling training sets and corpuses
Easily extensible with client data, schema
Types Concepts Annotations Text
Disjointedness Aggregations Restrictions
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KBpedia StatisticsArea Value
Knowledge bases Six (6) core 20 extended Domain-specific
Concepts (classes) 39 K ‘core’ reference concepts 138 K in standard Client-specific
Entities 32,000 K standard entities Client-specific
Assertions 3,700,000 K direct 6,500,000 K total (w/ inferred)
Analyzable text
Full articles Descriptions Titles Semsets Links Categories Infoboxes See also Multiple (200+) languages
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KBpedia Use Cases Document-specific word2vec training corpuses Text classification using ESA and SVM Dynamic machine learning using the KBpedia
knowledge graph Leveraging KBpedia
‘aspects’ to generate training sets automatically Benefits from extending KBpedia with private datasets Mapping external data and schema For latest list, see Cognonto use cases
III. How is it Constructed?
TM
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Cognonto Technology
Graph management Tagging Classification Mapping Domain integration
Build, update scripts Consistency, logic checks Graph expansion scripts Bespoke data structures
See text
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KBpedia Knowledge Ontology (KKO) Upper level of knowledge graph Based on CSP’s universal categories (Firstness,
Secondness, Thirdness) A ‘speculative grammar’ geared to KBAI ~ 165 concepts Tie-in points to ~ 80 typologies (~ 30 “core”) Open source
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KKO Top Three Branches (structure)I. Monads
II. Particulars
III. Generals
Monads are the idea space or building blocks of the ontology. Monads are potentials or possibilities, and are indivisible (‘indecomposable’) in
and of themselves. This category is a Firstness.
Particulars are actual or existing things (‘entities’) or events, also known as instances or individuals. Particulars become evident through a dyadic
action-reaction relation. This category is a Secondness.
Generals arise from placing particulars into natural classes or types; they are what mediates the commonalities or ‘laws’ among similar particulars.
Generals are real constructs, though are not actual. New knowledge arises from generalization. This category is a Thirdness.
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KKO Monads Branch (1ns)Monads [1ns]
FirstMonads [1ns]
Suchness [1ns]
Thisness [2ns]
Pluralness [3ns]
DyadicMonads [2ns]
Attributives [1ns]
Relatives [2ns]
Indicatives [3ns]
TriadicMonads [3ns]
Representation [1ns]
Mediation [2ns]
Mentation [3ns]
For complete branch: http://cognonto.com/docs/kko-upper-structure/
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KKO Particulars Branch (2ns)Particulars [2ns]
MonadicDyads [1ns]
MonoidalDyad [1ns]
EssentialDyad [2ns]
InherentialDyad [3ns]
Events [2ns]
Action [1ns]
Reaction [2ns]
Continuous [3ns]
Entities [3ns]
SingleEntities [1ns]
PartOfEntities [2ns]
ComplexEntities [3ns]For complete branch: http://cognonto.com/docs/kko-upper-structure/
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KKO Generals Branch (3ns)Generals [3ns](== SuperTypes)
SignElements [1ns]
AttributeTypes [1ns]
RelationTypes [2ns]
Symbols [3ns]
Constituents [2ns]
NaturalPhenomena [1ns]
SpaceTypes [2ns]
TimeTypes [3ns]
Manifestations [3ns]
NaturalMatter [1ns]
OrganicMatter [2ns]
Symbolic [3ns]For complete branch: http://cognonto.com/docs/kko-upper-structure/
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KBpedia’s Speculative Grammar (1ns)
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KBpedia’s Typologies
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KBpedia’s 32 ‘Core’ Typologies
Natural Phenomena Chemistry Products
Area or Region Organic Chemistry Food or Drink
Location or Place Biochemical Processes Drugs
Shapes Prokaryotes Facilities
Forms Protists & Fungus Audio Info
Activities Plants Visual Info
Events Animals Written Info
Times Diseases Structured Info
Situations Persons Finance & Economy
Atoms and Elements Organizations Society
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An Expandable Typology Design
Collapsed Tree Expanded Tree
32+ K entity types presently available
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Extending with Domain Schema
Becomes the basis for domain ML
IV. Why it Offers New Ontological Choices
TM
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Context and Perspective Knowledge is change, dynamic, emergent Knowledge is meaning Too many upper ontologies dichotomous:
abstract v tangible endurant v perdurant
Perspective, context requires a thirdness
particulars v universals 3D v 4D
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Treatment of Events Are events:
actions ? particulars ? objects ? entities ? instances ?
See Stanford Encyclopedia of Philosophy’s Events entry What is relationship of events to actions, activities? the
relationship to predicates? What is a situtation? what is a state?
properties ? attributes ? facts ? perdurants ? times ?
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Action Model
Events are particulars (1ns, in a monadic context) Activities: general, durative events (2ns, in a dyadic context) Processes: multiple activity durative events (3ns, this context)
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Separation of Dyadic Relations Attributives
Inherent characteristics of particulars:• Oneness• Otherness• Inherent
Relatives Non-inherent relationships:
• Concurrents (A:A, mostly, internal ObjectProperties) (generally, included with Attributes)
• Opposites (A:B, simple external)• Conjunctives
Indicatives Non-assertive, but do direct attention:
• Iconic• Indexical• Associative
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The Mindset of ‘Thirdness’Firstness Secondness Thirdness
hic et nunc
quality reaction mediation
one here and now eternal
possibility fact law
inheres adheres coheres
being existence external
purity action conduct
beginning occurrence diffusion
original dependence continuity
feeling consciousness thought
qualia particularity generality
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The Process of Categorization
Determine if existing category needs splitting: imbalance in size emergences (!)
If so, look to the 3ns of the category and:1. Determine the vocabulary (“building blocks”) for the new space
Firstness2. Determine the particular real things and events for the space
Secondness3. Determine the laws, regularities, generalities for the new space
Thirdness4. Name and populate the three new sub-categories
“The fundamental principles of formal logic are not properly axioms, but definitions and divisions; and the only facts which it contains relate to the identity of the
conceptions resulting from those processes with certain familiar ones.” (CP 3.149)
new mappings new knowledge
V. Open Discussion
TM
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Additional Potentials Mapping to more knowledge bases Exposing more structural features Peircean-based semantic parsers ML using graph structure, analytics Dynamic and reinforcement learning Continued ‘snake eating its tail’ Further typology structuring of attributes and
relations actual data values
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Issues, Open Topics Qualifying types by Firstness, Secondness The application of Thirdness to Firstness and
Secondness Treatment of dyadic relatives (attributes split)
(Nomenclature and Divisions of Dyadic Relations, 1903) Treatment of values and quantities Placement, treatment of ethics and aesthetics (e.g.,
goodness and beauty) Continued Peircean scholarship further refinements
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Ten Writingsi. ‘Cognonto is on the Hunt for Big AI Game’
ii. ‘The Irreducible Truth of Threes’
iii. ‘A Foundational Mindset: Firstness, Secondness, Thirdness’
iv. ‘Threes All of the Way Down to Typologies’
v. ‘A Speculative Grammar for Knowledge Bases’
vi. ‘How Fine Grained Can Entity Types Get?’
vii. ‘Rationales for Typology Designs in Knowledge Bases’
viii. ‘A (Partial) Taxonomy of Machine Learning Features’
ix. ‘Gold Standards in Enterprise Knowledge Projects’
x. ‘“Natural Classes” in the Knowledge Web’
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NASCAR Stickers
http://cognonto.com (demo + interactive knowledge graph)
https://github.com/cognonto/kko (KKO)
http://www.mkbergman.com/category/kbai/
http://mkbergman.com
http://fgiasson.com/blog
http://structureddynamics.com
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