"Objective fiction: the semantic construction of web reality" talks about current challenges for semantic technologies, and the Semantic Web in particular, focusing on cognitive and social dimensions of human semantics.
This tutorial tries to answer the following questions:
What is the best practice for ontology reuse?
Is it fine to use external ontology entities to model my local entities?
Should I import the ontologies that I reuse?
What if I only need a part of an ontology?
What if an external ontology that I reused, changes?
Different Semantic Perspectives for Question Answering SystemsAndre Freitas
Question Answering systems define one of the most complex tasks in computational semantics. The intrinsic complexity of the QA task allows researchers of QA systems to investigate and explore different perspectives of semantics. However, this complexity also induces a bias towards a systems perspective, where researchers are alienated from a deeper reasoning on the semantic principles that are in place within the different components of the system. In this talk we will explore the semantic challenges, principles and perspectives behind the components of QA systems, aiming at providing a principled map and overview on the contribution of each component within the QA semantic interpretation goal.
"Objective fiction: the semantic construction of web reality" talks about current challenges for semantic technologies, and the Semantic Web in particular, focusing on cognitive and social dimensions of human semantics.
This tutorial tries to answer the following questions:
What is the best practice for ontology reuse?
Is it fine to use external ontology entities to model my local entities?
Should I import the ontologies that I reuse?
What if I only need a part of an ontology?
What if an external ontology that I reused, changes?
Different Semantic Perspectives for Question Answering SystemsAndre Freitas
Question Answering systems define one of the most complex tasks in computational semantics. The intrinsic complexity of the QA task allows researchers of QA systems to investigate and explore different perspectives of semantics. However, this complexity also induces a bias towards a systems perspective, where researchers are alienated from a deeper reasoning on the semantic principles that are in place within the different components of the system. In this talk we will explore the semantic challenges, principles and perspectives behind the components of QA systems, aiming at providing a principled map and overview on the contribution of each component within the QA semantic interpretation goal.
Ontology and Ontology Libraries: a Critical StudyDebashisnaskar
The concept of digital library revolutionized its popularity with the development of networking technology. Digital library stores various kind of documents in digitized format that enables user smooth access to these documents at subsidized costs. In the recent past, a similar concept i.e., ontology library has gained popularity among the communities like semantic web, artificial intelligence, information science, philosophy, linguistics, and so forth.
study or concern about what kinds of things exist
what entities there are in the universe.
the ontology derives from the Greek onto (being) and logia (written or spoken). It is a branch of metaphysics , the study of first principles or the root of things.
On the Semantic Mapping of Schema-agnostic Queries: A Preliminary StudyAndre Freitas
The growing size, heterogeneity and complexity of databases
demand the creation of strategies to facilitate users and systems to consume
data. Ideally, query mechanisms should be schema-agnostic or
vocabulary-independent, i.e. they should be able to match user queries
in their own vocabulary and syntax to the data, abstracting data consumers
from the representation of the data. Despite being a central requirement across natural language interfaces and entity search, there is a lack on the conceptual analysis of schema-agnosticism and on the associated semantic differences between queries and databases. This work aims at providing an initial conceptualization for schema-agnostic queries aiming at providing a fine-grained classification which can support the scoping, evaluation and development of semantic matching approaches for schema-agnostic queries.
Word Tagging with Foundational Ontology ClassesAndre Freitas
Semantic annotation is fundamental to deal with large-scale
lexical information, mapping the information to an enumerable set of
categories over which rules and algorithms can be applied, and foundational
ontology classes can be used as a formal set of categories for
such tasks. A previous alignment between WordNet noun synsets and
DOLCE provided a starting point for ontology-based annotation, but in
NLP tasks verbs are also of substantial importance. This work presents
an extension to the WordNet-DOLCE noun mapping, aligning verbs according
to their links to nouns denoting perdurants, transferring to the
verb the DOLCE class assigned to the noun that best represents that
verb’s occurrence. To evaluate the usefulness of this resource, we implemented
a foundational ontology-based semantic annotation framework,
that assigns a high-level foundational category to each word or phrase
in a text, and compared it to a similar annotation tool, obtaining an
increase of 9.05% in accuracy.
Deep Learning for Information Retrieval: Models, Progress, & OpportunitiesMatthew Lease
Talk given at the 8th Forum for Information Retrieval Evaluation (FIRE, http://fire.irsi.res.in/fire/2016/), December 10, 2016, and at the Qatar Computing Research Institute (QCRI), December 15, 2016.
Practical Machine Learning - Part 1 contains:
- Basic notations of ML (what tasks are there, what is a model, how to measure performance)
- A couple of examples of problems and solutions (taken from previous work)
- A brief presentation of open-source software used for ML (R, scikit-learn, Weka)
Exploring Session Context using Distributed Representations of Queries and Re...Bhaskar Mitra
Search logs contain examples of frequently occurring patterns of user reformulations of queries. Intuitively, the reformulation "san francisco" → "san francisco 49ers" is semantically similar to "detroit" →"detroit lions". Likewise, "london"→"things to do in london" and "new york"→"new york tourist attractions" can also be considered similar transitions in intent. The reformulation "movies" → "new movies" and "york" → "new york", however, are clearly different despite the lexical similarities in the two reformulations. In this paper, we study the distributed representation of queries learnt by deep neural network models, such as the Convolutional Latent Semantic Model, and show that they can be used to represent query reformulations as vectors. These reformulation vectors exhibit favourable properties such as mapping semantically and syntactically similar query changes closer in the embedding space. Our work is motivated by the success of continuous space language models in capturing relationships between words and their meanings using offset vectors. We demonstrate a way to extend the same intuition to represent query reformulations.
Furthermore, we show that the distributed representations of queries and reformulations are both useful for modelling session context for query prediction tasks, such as for query auto-completion (QAC) ranking. Our empirical study demonstrates that short-term (session) history context features based on these two representations improves the mean reciprocal rank (MRR) for the QAC ranking task by more than 10% over a supervised ranker baseline. Our results also show that by using features based on both these representations together we achieve a better performance, than either of them individually.
Paper: http://research.microsoft.com/apps/pubs/default.aspx?id=244728
In this presentation we discuss several concepts that include Word Representation using SVD as well as neural networks based techniques. In addition we also cover core concepts such as cosine similarity, atomic and distributed representations.
What one needs to know to work in Natural Language Processing field and the aspects of developing an NLP project using the example of a system to identify text language
Detecting and Describing Historical Periods in a Large CorporaTraian Rebedea
Many historic periods (or events) are remembered
by slogans, expressions or words that are strongly linked to them. Educated people are also able to determine whether a particular word or expression is related to a specific period in human history. The present paper aims to establish correlations between significant historic periods (or events) and the texts written in that period. In order to achieve this, we have developed a system that automatically links words (and topics discovered using Latent Dirichlet Allocation) to periods of time in the recent history. For this analysis to be relevant and conclusive, it must be undertaken on a representative set of texts written throughout history. To this end, instead of relying on manually selected texts, the Google Books Ngram corpus has been chosen as a basis for the analysis. Although it provides only word n-gram statistics for the texts written in a given year, the resulting time series can be used to provide insights about the most important periods and events in recent history, by automatically linking them with specific keywords or even LDA topics.
Ontology and Ontology Libraries: a Critical StudyDebashisnaskar
The concept of digital library revolutionized its popularity with the development of networking technology. Digital library stores various kind of documents in digitized format that enables user smooth access to these documents at subsidized costs. In the recent past, a similar concept i.e., ontology library has gained popularity among the communities like semantic web, artificial intelligence, information science, philosophy, linguistics, and so forth.
study or concern about what kinds of things exist
what entities there are in the universe.
the ontology derives from the Greek onto (being) and logia (written or spoken). It is a branch of metaphysics , the study of first principles or the root of things.
On the Semantic Mapping of Schema-agnostic Queries: A Preliminary StudyAndre Freitas
The growing size, heterogeneity and complexity of databases
demand the creation of strategies to facilitate users and systems to consume
data. Ideally, query mechanisms should be schema-agnostic or
vocabulary-independent, i.e. they should be able to match user queries
in their own vocabulary and syntax to the data, abstracting data consumers
from the representation of the data. Despite being a central requirement across natural language interfaces and entity search, there is a lack on the conceptual analysis of schema-agnosticism and on the associated semantic differences between queries and databases. This work aims at providing an initial conceptualization for schema-agnostic queries aiming at providing a fine-grained classification which can support the scoping, evaluation and development of semantic matching approaches for schema-agnostic queries.
Word Tagging with Foundational Ontology ClassesAndre Freitas
Semantic annotation is fundamental to deal with large-scale
lexical information, mapping the information to an enumerable set of
categories over which rules and algorithms can be applied, and foundational
ontology classes can be used as a formal set of categories for
such tasks. A previous alignment between WordNet noun synsets and
DOLCE provided a starting point for ontology-based annotation, but in
NLP tasks verbs are also of substantial importance. This work presents
an extension to the WordNet-DOLCE noun mapping, aligning verbs according
to their links to nouns denoting perdurants, transferring to the
verb the DOLCE class assigned to the noun that best represents that
verb’s occurrence. To evaluate the usefulness of this resource, we implemented
a foundational ontology-based semantic annotation framework,
that assigns a high-level foundational category to each word or phrase
in a text, and compared it to a similar annotation tool, obtaining an
increase of 9.05% in accuracy.
Deep Learning for Information Retrieval: Models, Progress, & OpportunitiesMatthew Lease
Talk given at the 8th Forum for Information Retrieval Evaluation (FIRE, http://fire.irsi.res.in/fire/2016/), December 10, 2016, and at the Qatar Computing Research Institute (QCRI), December 15, 2016.
Practical Machine Learning - Part 1 contains:
- Basic notations of ML (what tasks are there, what is a model, how to measure performance)
- A couple of examples of problems and solutions (taken from previous work)
- A brief presentation of open-source software used for ML (R, scikit-learn, Weka)
Exploring Session Context using Distributed Representations of Queries and Re...Bhaskar Mitra
Search logs contain examples of frequently occurring patterns of user reformulations of queries. Intuitively, the reformulation "san francisco" → "san francisco 49ers" is semantically similar to "detroit" →"detroit lions". Likewise, "london"→"things to do in london" and "new york"→"new york tourist attractions" can also be considered similar transitions in intent. The reformulation "movies" → "new movies" and "york" → "new york", however, are clearly different despite the lexical similarities in the two reformulations. In this paper, we study the distributed representation of queries learnt by deep neural network models, such as the Convolutional Latent Semantic Model, and show that they can be used to represent query reformulations as vectors. These reformulation vectors exhibit favourable properties such as mapping semantically and syntactically similar query changes closer in the embedding space. Our work is motivated by the success of continuous space language models in capturing relationships between words and their meanings using offset vectors. We demonstrate a way to extend the same intuition to represent query reformulations.
Furthermore, we show that the distributed representations of queries and reformulations are both useful for modelling session context for query prediction tasks, such as for query auto-completion (QAC) ranking. Our empirical study demonstrates that short-term (session) history context features based on these two representations improves the mean reciprocal rank (MRR) for the QAC ranking task by more than 10% over a supervised ranker baseline. Our results also show that by using features based on both these representations together we achieve a better performance, than either of them individually.
Paper: http://research.microsoft.com/apps/pubs/default.aspx?id=244728
In this presentation we discuss several concepts that include Word Representation using SVD as well as neural networks based techniques. In addition we also cover core concepts such as cosine similarity, atomic and distributed representations.
What one needs to know to work in Natural Language Processing field and the aspects of developing an NLP project using the example of a system to identify text language
Detecting and Describing Historical Periods in a Large CorporaTraian Rebedea
Many historic periods (or events) are remembered
by slogans, expressions or words that are strongly linked to them. Educated people are also able to determine whether a particular word or expression is related to a specific period in human history. The present paper aims to establish correlations between significant historic periods (or events) and the texts written in that period. In order to achieve this, we have developed a system that automatically links words (and topics discovered using Latent Dirichlet Allocation) to periods of time in the recent history. For this analysis to be relevant and conclusive, it must be undertaken on a representative set of texts written throughout history. To this end, instead of relying on manually selected texts, the Google Books Ngram corpus has been chosen as a basis for the analysis. Although it provides only word n-gram statistics for the texts written in a given year, the resulting time series can be used to provide insights about the most important periods and events in recent history, by automatically linking them with specific keywords or even LDA topics.
The DiNAR Project: Meaningful Mixed Reality for Heritage - Gareth BealeMuseums Computer Group
Gareth Beale, researcher at Centre for Digital Heritage/Digital Creativity Labs (University of York), presents 'The DiNAR Project: Meaningful Mixed Reality for Heritage' at the Museum Computer Group (MCG) Spring Event 2016 - 'Life with Digital Projects' #MCGProjects
WG RDA/WDS Publishing Data Workflows - P6 meeting session - 10 minute presentation on BioSharing and how it can help researchers, journal editors, funders, standard developers and database curators make sense of the sea of standards and databases in the life sciences.
[3.8] Archiving and Publishing in Practice Event Logs - Joos Buijs [3TU.Datac...3TU.Datacentrum
3TU.Datacentrum Symposium Research Data Management:
Funder requirements, Questions and Solutions
At this symposium the funding organisation NWO and the European Commission explained their vision, plans and requirements. Researchers from the three universities of technology shared their experiences of data management in different stages of research. And the Research Data Services team informed the audience about research data management services offered by 3TU.Datacentrum.
The 3TU.Datacentrum symposium took place at the TU Delft (26 May), University of Twente (2 June) and TU Eindhoven (11 June) for and with local researchers.
More information on: datacentrum.3tu.nl/over-3tudatacentrum/symposium-2014
Summary slides from my recent short presentation at Interrogating Infrastructure: A Symposium Hosted by King’s Digital Lab and the Department of Digital Humanities, King’s College London, July 8th, 2016
ePADD and Access -- Society of American Archivists (SAA) Annual Meeting, 2015Josh Schneider
Presentation delivered at the Society of American Archivists (SAA) Annual Meeting, 2015, in a session titled "Out of the Frying Pan and into the Reading Room: Approaches to Serving Electronic Records."
ePADD is a software package developed by Stanford University's Special Collections & University Archives that supports archival processes around the appraisal, ingest, processing, discovery, and delivery of email archives. More information, including links to the software, user guide, and community forums, can be found at https://library.stanford.edu/projects/epadd.
The FP7 Post-Grant Open Access Pilot: An All-Encompassing Gold Open Access Fu...OpenAIRE
A year into the EC FP7 Post-Grant Open Access Pilot, this presentation delivered at the LIBER Annual Conference 2016 in Helsinki shows the current progress of this funding initiative. This Gold OA Pilot has currently two funding worklines, a main one for APC/BPC payments for post-grant manuscripts arising from finished FP7 projects and an alternative funding mechanism for supporting APC-free OA journals and platforms. Detailed figures are provided for the APC payments made so far, together with a number of findings the initiative has already come upon.
As service providers and primary code contributors in the Islandora Community, discoverygarden encounters customers who are ingesting, accessing, and storing high volumes of data. For example, a customer who had 150,000 objects in 2012 now has three million objects and expectations to grow to five million in the very short term. This is increasingly common.
As repositories grow in size they can encounter poor performance, particularly during large ingests and derivative generation. To accommodate growing repositories caching mechanisms, infrastructure changes, and code updates are necessary.
The presentation will explore customer case studies that demonstrate interim solutions and the extensive, ongoing research and development to find long-term solutions.
Imperial College London - journey to open scholarshipTorsten Reimer
Talk given at the 2016 Open Repositories conference in Dublin, Ireland. This paper follows the journey of a research intensive university towards making its outputs available openly, discusses approaches outlined above and identifies problems in the global scholarly communications landscape.
Research methodology (Philosophies and paradigms) in ArabicAmgad Badewi
Explaining research philosophies and paradigms. Explaining the ontology, epistemology and of different research paradigms. In addition, explaining how to innovate in research using pragmatic research. Finally, explaining Grounded Theory at the end of it.
Configuring patterns for systemic design - PUARL 2018 conferenceHelene Finidori
This was presented at the PUARL 2018 conference, in the context of the evolution of pattern languages, and of the discussion of how much needs to be ‘changed’ in current approaches to address current and future design issues.
It is an exploration on how patterns and pattern languages could be structured and used to tackle wicked societal problems.
I am looking into the qualities and properties of patterns in relation to embodied cognition and systems; revisiting the problem-solution connection and association; examining generativity and ways to sort out entangled mechanisms at various levels and scales; questioning the extend of the act of design, and the role and responsibility of the designer; and suggesting ways forward.
Qualitative Studies in Software Engineering - Interviews, Observation, Ground...alessio_ferrari
This
Lecture about qualitative data collection methods and qualitative data analysis in software engineering. Topics covered are:
1. Sampling
2. Interviews
3. Observation and Participant Observation
4. Archival Data Collection
5. Grounded theory, Coding, Thematic Analysis
6. Threats to validity in qualitative studies
Find the videos at: https://www.youtube.com/playlist?list=PLSKM4VZcJjV-P3fFJYMu2OhlTjEr9Bjl0
Fueling the future with Semantic Web patterns - Keynote at WOP2014@ISWCValentina Presutti
I will claim that Semantic Web Patterns can drive the next technological breakthrough: they can be key for providing intelligent applications with sophisticated ways of interpreting data. I will picture scenarios of a possible not so far future in order to support my claim. I will argue that current Semantic Web Patterns are not sufficient for addressing the envisioned requirements, and I will suggest a research direction for fixing the problem, which includes the hybridisation of existing computer science pattern-based approaches, and human computing.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...
Knowledge Patterns SSSW2016
1. Knowledge Patterns:
Design and Extraction
Aldo Gangemi1,2,
joint work with Andrea Giovanni Nuzzolese2,
Valentina Presutti2, Diego Reforgiato Recupero2,3
1LIPN, Paris Nord University, CNRS UMR7030, France
2Semantic Technology Lab, ISTC-CNR, Rome, Italy
3Department of Informatics, University of Cagliari, Italy
aldo.gangemi@lipn.univ-paris13.fr,
{andrea.nuzzolese,valentina.presutti,diego.reforgiato}@istc.cnr.it
2. Invariances
• “The important things in the world appear as invariants […] of
[…] transformations” (P. Dirac, The principles of quantum
mechanics, 1947)
• “A property or relationship is objective when it is invariant
under the appropriate transformations” (R. Nozick,
Invariances, 2001)
• Multiple presentations (≈ under mapping)
• Multiple stages (≈ under change)
• Multiple contexts / perceivers / interpreters (≈ under different
reference frameworks)
3. Patterns in general
• “Invariances across observed data or objects”
• They exist in natural, social, cognitive, or abstract worlds
• Mathematical pattern science is about symbols, i.e. non-
interpreted information objects
• Objects of knowledge engineering are interpreted (cognitively,
and, by derivation, formally)
• Mutual support/dependencies
• Gibson (1966), Shepard (1987,1992): invariances in stimulus-
energy pair permanent (“projectable”) properties in the
environment (affordances)
• E.g. colors, shapes, features of entities can constitute value-
added references for behaviour
4. Knowledge as memory of (value-laden)
observable (ir)regularities?
Cure
Healer
Medication
Patient
6. At the origins of modern ontologies:
Pat Hayes’ naïve physics manifesto
7.
8. A Translation Approach to
Portable Ontology
Specifications. T. R. Gruber,
Knowledge Acquisition, 5(2):
199-220, 1993.
15459 citations!!!
9. CLib Attach component
(Attach has
(superclasses (Action))
(required-slot (object base))
(primary-slot (agent)) )
(every Attach has
(object ((exactly 1 Tangible-Entity) (a Tangible-Entity)))
(base ((exactly 1 Tangible-Entity) (a Tangible-Entity)))
(every Attach has
(preparatory-event ((:default
(a Make-Contact with
(object ((the object of Self)))
(base ((the base of Self))))
(a Detach with
(object ((the object of Self)))
(base ((the base of Self)))) ))))
RCC-8 Spatial Ontology
RCC: a calculus for region based
qualitative spatial reasoning
AG Cohn, B Bennett, JM Gooday, N Gotts -
GeoInformatica, 1997
A library of generic concepts for
composing knowledge bases
K Barker, B Porter, P Clark, 2001
10. DOLCE (S5) foundational
ontology patterns
Sowa’s Peirce-inspired
top-level ontology
Sweetening ontologies with DOLCE
A Gangemi, N Guarino, C Masolo, A Oltramari, …,
2002 - Springer
Knowledge Representation: Logical,
Philosophical, and Computationa Foundations
J SOWA - Brooks/Cole, 2000
11. Evidence of knowledge patterns
• In linguistic resources
– Sentence forms
– Sub-categorization frames
– Lexico-syntactic patterns
– Conceptual frames
– Question patterns
– (Bounded sets of) selectional preferences
• In data
– Data patterns
– Data models (xsd, rdb)
– Query types and views
– Microformats
– Infoboxes
• In interaction
– Interaction patterns
– Lenses
– HTML templates
• In semantic resources
– Competency questions
– n-ary relations
– OWL/RDFS classes with (locally complete?)
sets of restrictions or properties
– KM Component Library
– Content ontology design patterns (CPs)
– Knowledge patterns discovered from datasets
12. ConceptNet
MIT OpenMind common sense project
AtLocation(dog, kennel)[]
CapableOf(dog, bark)[]
CapableOf(dog, guard house)[]
CapableOf(dog, pet)[]
CapableOf(dog, run)[]
Desires(dog, bone)[]
Desires(dog, chew bone)[]
Desires(dog, pet)[]
Desires(dog, play)[]
HasA(dog, flea)[]
HasA(dog, four leg)[]
HasA(dog, fur)[]
HasProperty(dog, loyal)[]
IsA(dog, canine)[]
IsA(dog, domesticate animal)[]
IsA(dog, loyal friend)[]
IsA(dog, mammal)[]
IsA(dog, man best friend)[]
IsA(dog, pet)[]
UsedFor(dog, companionship)[]
ConceptNet—a practical
commonsense reasoning tool-kit.
Liu, Hugo, and Push Singh, BT
technology journal, 2004
14. VerbNet Motion verb class
VerbNet: A broad-coverage, comprehensive verb lexicon. Schuler, KK, 2005
15. Knowledge patterns as expertise units
• Evidence that units of expertise are larger than what we have from average linked data triples, or
ontology learning
• Cf. cognitive scientist Dedre Gentner: “uniform relational representation is a hallmark of expertise”
• We need to create expertise-oriented boundaries unifying multiple triples
– “Competency questions” are used to link ontology design patterns to requirements:
•Which objects take part in a certain event?
•Which tasks should be executed in order to achieve a certain goal?
• What’s the function of that artifact?
•What norms are applicable to a certain case?
•What inflammation is active in what body part with what morphology?
– Sometimes exception conditions should be added
– Task-based ontology evaluation can be performed with unit tests against ontologies trying to satisfy
competency questions
Relational language and the development of relational mapping. Loewenstein, J, Gentner, D. Cognitive psychology, 2005
16. quality, patterns
The role of competency questions
in enterprise engineering
M Grüninger, MS Fox - Benchmarking—Theory
and Practice, 1995 - Springer
Modelling ontology
evaluation and validation
A Gangemi, C Catenacci, M Ciaramita, J
Lehmann - 2006 - Springer
Evaluating ontological
decisions with OntoClean
N Guarino, C Welty - Communications of
the ACM, 2002 - dl.acm.org
Ontology design patterns
A Gangemi, V Presutti - Handbook on
ontologies 2nd ed., 2009 - Springer
17. Ontology Design Patterns
An ontology design
pattern is a reusable
successful solution to
a recurrent modeling
problem
Visit www.ontologydesignpatterns.org
18. Maximal ontology design requirement:
What are we talking about, and why?
Generic Competency Questions Specific Modelling Use Case
Who does what, when and where? Production reports, schedules
Which objects take part in a certain event? Resource allocation, biochemical pathways
What are the parts of something? Component schemas, warehouse management
What’s an object made of? Drug and food composition, e.g. for safety (comp.)
What’s the place of something? Geographic systems, resource allocation
What’s the time frame of something? Dynamic knowledge bases
What technique, method, practice is being used? Instructions, enterprise know-how database
Which tasks should be executed in order to achieve a certain goal? Planning, workflow management
Does this behaviour conform to a certain rule? Control systems, legal reasoning services
What’s the function of that artifact? System description
How is that object built? Control systems, quality check
What’s the design of that artifact? Project assistants, catalogues
How did that phenomenon happen? Diagnostic systems, physical models
What’s your role in that transaction? Activity diagrams, planning, organizational models
What that information is about? How is it realized? Information and content modelling, computational models, subject
directories
What argumentation model are you adopting for negotiating an agreement? Cooperation systems
What’s the degree of confidence that you give to this axiom? Ontology engineering tools
19. Layered pattern morphisms
An ontology design pattern describes a formal expression
that can be exemplified, morphed, instantiated, and expressed in
order to solve a domain modelling problem
• owl:Class:_:x rdfs:subClassOf owl:Restriction:_:y
• Inflammation rdfs:subClassOf (localizedIn some BodyPart)
• Colitis rdfs:subClassOf (localizedIn some Colon)
• John’s_colitis isLocalizedIn John’s_colon
• “John’s colon is inflammated”,“John has got colitis”,“Colitis is the inflammation
of colon”
Logical
Pattern
(MBox)
Generic
Content
Pattern
(TBox)
Specific
Content
Pattern
(TBox)
Data
Pattern
(ABox)
exemplifiedAs morphedAs instantiatedAs Linguistic
Pattern
expressedAs
Logic Meaning Reference Expression
expressedAs
Abstraction
Aldo Gangemi,Valentina Presutti: Ontology Design Patterns. Handbook on Ontologies 2nd ed. (2009)
20. Problem example:
Temporal n-ary patterns
• Temporal indexing pattern
– (R(a,b))+t sentence indexing
• quads, external time stamps
– R(a,b)+t relation indexing
• reified n-ary relations (3D frames)
– R(a+t,b+t) individual indexing
• fluents, 4D, tropes,“context slices” (4D frames)
– tR name nesting
• ad hoc naming of binary relations
• More indexes for additional arguments
A Multi-dimensional Comparison of Ontology Design Patterns for Representing
n-ary Relations. A Gangemi,V Presutti. SOFSEM 2013: 86-105
An Empirical Perspective on Representing Time. A Scheuermann, E Motta, P
Mulholland, A Gangemi andV Presutti. K-CAP 2013
Formal Unifying Standards for the
Representation of Spatiotemporal
Knowledge.
P. Hayes, Advanced Decision
Architectures Alliance, 2004
21. Procedural patterns
• Precise
– Classification
– Subsumption
– Inheritance
– Materialization
– Rule firing
– Constructive query
• Approximate
– Fuzzy classification
– Information extraction (NER, RE)
– Similarity induction (e.g. alignment)
– Taxonomy induction
– Relevance detection
– Latent semantic indexing
• Thesaurus to SKOS
• Relational DB to RDF
• WordNet RDB to OWL
• XML to RDF
• FrameNet XML to RDF
• Microformat to RDF
• NER entities to ABox
• NLP to RDF
Reasoning patterns
Alignment patterns
Reengineering patterns
22. Anti-patterns (1/2)
• Partonomies or subject classifications as subsumption hierarchies
• *City subClassOf Country
• City subClassOf (partOf some Country)
• *City subClassOf Geography
• City broader Geography (e.g. in SKOS)
• Linguistic disjunction as class disjointness
• Dead or alive
• *Dead or Alive
• Dead disjointWith Alive
• Linguistic conjunction as class disjunction
• Pen and paper
• *Pen and Paper
• Pen or Paper | Collection subClassOf (hasMember some Paper ; some Pen)
A catalogue of OWL ontology
antipatterns.
Roussey, Corcho, Vilches-Blázquez,
ACM, 2009.
A user oriented owl development
environment designed to implement
common patterns and minimise common
errors. Horridge, Rector, Drummond,
Springer, 2004.
23. Anti-patterns (2/2)
• Causality as entailment
• Kaupthing bank behavior caused Iceland crisis
• *KaupthingBankBehavior subClassOf IcelandCrisis
• KaupthingBankBehavior isCauseOf IcelandCrisis
• Expressions as instances of the class representing their meaning
• *dog(word) rdf:type Dog
• dog(word) expresses Dog (with punning)
• Multiple domains or ranges of properties as intersection
• *hasInflammation rdfs:domain Epithelium ; Endothelium
• hasInflammation rdfs:domain (Epithelium or Endothelium)
24.
25. Putting the pieces
together
“Mine & Design”
pattern induction from data
cleaning data by using (foundational) patterns
pattern-based knowledge extraction from text
axiom induction from knowledge graphs
…
26. Pattern induction from data:
centrality discovery in datasets
mo:Track
mo:MusicArtist
mo:Playlist
mo:Torrent
mo:ED2K
tags:Tag
mo:Record
foaf:maker
rdfs:Literal
dc:title
dc:datemo:image
dc:description
mo:track
tags:taggedWithTag
mo:available_as
mo:available_as
mo:available_as
Extracting Core Knowledge from
Linked Data.
Presutti, Aroyo et al., COLD2011.
27. Serving DBpedia with DOLCE–More than Just Adding a Cherry on Top. Paulheim, Gangemi, ISWC, 2015.
28.
29.
30.
31. Information Extraction and the SW
• Historically SW mainly worked on ontology learning
– unconvincing results: sparseness, core knowledge difficult to
catch, etc. (cf. analyses in Coppola et al. 2009, Blomqvist, 2009)
– natural language understanding known to be an AI-complete
problem
• The paradigm of Open Information Extraction (Etzioni, 2006) fits the
lightweight and/or data-driven trend of current SW
• Semantic technologies need hybridization
31
Google Knowledge Graph
IBM Watson
QA, NL querying on LD,
full text search jointly with
queries, ...
Apple Siri, Google Now, SRI
startup Desti
Facebook Social Graph
Microsoft Cortana
OIE, NELL, BabelNet, ...
32.
33. Stochasticity does it well?
• Purely stochastic approaches to NLU attempt to
learn models that solve one specific problem, but
how to compose the different models? How to
hybridise those models with logic/knowledge-
based approaches?
• Cf. NCM chatbot, MetaMind neural QA
34. Google’s “Neural Conversational Model”
one year ago on arXiv
mixed magic and
massive stupidity
in this model
deeply learnt from
open movie scripts
38. • The Black Hand might not have decided to
barbarously assassinate Franz Ferdinand after
he arrived in Sarajevo on June 28th, 1914
event
negation
modality
participants
more participants
quality
coreference
deep semantic parsing:
not just annotation, but
formal knowledge extraction
event
relation
39. Open Information Extraction
pc5: NLPapps mac$ java -Xmx512m -jar reverb-latest.jar <<<"The Black Hand might
not have decided to barbarously assassinate Franz Ferdinand after he arrived in
Sarajevo on June 28th, 1914."
Initializing ReVerb extractor...Done.
Initializing confidence function...Done.
Initializing NLP tools...Done.
Starting extraction.
stdin 1 he arrived in Sarajevo 13 14 14 16 16
10.2200632195721161 The Black Hand might not have decided to barbarously
assassinate Franz Ferdinand after he arrived in Sarajevo on June 28th , 1914 .
DT NNP NNP MD RB VB VBN TO RB VB NNP NNP IN PRP VBD IN NNP IN NNP JJ , CD .
B-NP I-NP I-NP B-VP I-VP I-VP I-VP I-VP I-VP I-VP B-NP I-NP B-SBAR B-NP B-VP
B-PP B-NP B-PP B-NP I-NP I-NP I-NP O he arrive in sarajevo
Done with extraction.
Summary: 1 extractions, 1 sentences, 0 files, 1 seconds
http://ai.cs.washington.edu/projects/
open-information-extraction
40. Open Knowledge Extraction
• Open Knowledge Extraction (OKE) is a hybrid approach to
knowledge graph production that exploits some of the assumptions
of Open Information Extraction (open-domain, unsupervised),
together with formal semantic reengineering of NLP output,
Semantic Web and Linked Data patterns, entity linking, word-sense
disambiguation linked to Linguistic Linked Data
• The result of OKE is a two-layered OWL-RDF knowledge graph that
(1) lifts the content of a text into entities grounded into public web
identities, with formal axioms, and (2) deeply annotates the text
• OKE can be used as a semantic middleware between content and
knowledge management: querying, annotating, classifying,
detecting, …
41. LOD and ODP design
Aligned to WordNet, VerbNet,
FrameNet, DOLCE+DnS,
DBpedia, schema.org, BabelNet
RESTful or motif-based
Python query interface
Earmark
RDF, OWL
Apache Stanbol
Neo-Davidsonian, DRT- and Frame-based
High EE and RE accuracy
FRED integrates
NER, SenseTagging, WSD, Taxonomy
Induction, Relation/Event/Role Extraction
NIF
ALCO(D) DL language
http://wit.istc.cnr.it/stlab-tools/fred
42. OKE w. FRED
“The Black Hand might not have decided to barbarously
assassinate Franz Ferdinand after he arrived in Sarajevo
on June 28th, 1914”
type induction
negation
modality
taxonomy induction
semantic roles
entity linking
+ configurable namespaces,
Earmark text spans with semiotic relations to graph entities (denotes, hasInterpretant),
NIF annotations and text segmentation
events
qualities
tense representation
second order relations
role propagation
predicate-argument structures
coreference resolution
48. <http://dbpedia.org/resource/Kind_of_Blue>
<http://www.w3.org/2000/01/rdf-schema#comment>
"Kind of Blue is a studio album by American jazz musician Miles Davis,
released on August 17, 1959, by Columbia Records. Recording sessions
for the album took place at Columbia's 30th Street Studio in New York City
on March 2 and April 22, 1959. The sessions featured Davis's ensemble
sextet, with pianist Bill Evans, drummer Jimmy Cobb, bassist Paul
Chambers, and saxophonists John Coltrane and Julian Cannonball
Adderley."@en .
describe dbpedia:Kind_of_Blue
<http://dbpedia.org/resource/Kind_of_Blue> <http://dbpedia.org/ontology/producer> <http://dbpedia.org/resource/Irving_Townsend> .
<http://dbpedia.org/resource/Kind_of_Blue> <http://purl.org/dc/terms/subject> <http://dbpedia.org/resource/Category:Albums_certified_gold_by_the_British_Phonographic_Industry> .
<http://dbpedia.org/resource/Kind_of_Blue> <http://dbpedia.org/ontology/recordDate> "1958-05-25+02:00"^^<http://www.w3.org/2001/XMLSchema#date> .
<http://dbpedia.org/resource/Kind_of_Blue> <http://dbpedia.org/ontology/recordedIn> <http://dbpedia.org/resource/CBS_30th_Street_Studio> .
<http://dbpedia.org/resource/Kind_of_Blue> <http://dbpedia.org/ontology/recordedIn> <http://dbpedia.org/resource/New_York_City> .
<http://dbpedia.org/resource/Kind_of_Blue> <http://dbpedia.org/ontology/recordLabel> <http://dbpedia.org/resource/Legacy_Recordings> .
<http://dbpedia.org/resource/Kind_of_Blue> <http://dbpedia.org/ontology/genre> <http://dbpedia.org/resource/Modal_jazz> .
<http://dbpedia.org/resource/Kind_of_Blue> <http://dbpedia.org/property/title> <http://dbpedia.org/resource/Blue_in_Green> .
<http://dbpedia.org/resource/Kind_of_Blue> <http://dbpedia.org/property/producer> <http://dbpedia.org/resource/Irving_Townsend> .
<http://dbpedia.org/resource/Kind_of_Blue> <http://dbpedia.org/property/title> <http://dbpedia.org/resource/All_Blues> .
<http://dbpedia.org/resource/Kind_of_Blue> <http://dbpedia.org/property/title> <http://dbpedia.org/resource/Freddie_Freeloader> .
Entity Linking
again
OKE again
49. “CBS 30th Street Studio was an American recording studio operated
by Columbia Records, and located at 207 East 30th Street, between
Second and Third Avenues in Manhattan, New York City.”
<http://dbpedia.org/resource/Columbia_Records> <http://www.ontologydesignpatterns.org/ont/fred/
domain.owl#operateBetweenAvenueLocatedIn> <http://dbpedia.org/resource/New_York_City> .
etc. …
Legalo synthetic path finder
50. Complexity of FRED’s models and
computational time
• typically, a 100-word sentence takes less than 1 second to be processed,
also considering the lag due to the Web API, and the load of a diagram
when using the Web application
• the expressivity of an OKE knowledge graph dataset produced by FRED
calculated from a composite text corpus from four different textual types
(approx. 19,000 axioms) is equivalent to an ALCO(D) (Attributive
Language with Complements, Object value restrictions and Data
properties) DL language
• ALCO(D) includes atomic negation, class intersection, universal and
existential restrictions, and nominals (closed world classes)
• computational complexity of ALCO(D) is PSpace-Complete, and enjoys
both finite model and tree model properties (cf. http://www.cs.man.ac.uk/
~ezolin/dl/ for a complexity navigator)
52. Four classes of semantic
problems
1. partial accuracy of specific NLP components lead to
global errors
2. “in praesentia” semantics besides literal interpretation:
various kinds of coercion, met* phenomena
3. “in absentia” semantics: implicatures, presuppositions,
tacit knowledge, reference to the physical context
4. higher-order phenomena: emergent frames, social
(and legal) norms, attitudes, argumentation, cultural
frames and narratives, discourse marks, text types
53. 1. Partial accuracy of specific NLP
components lead to global errors
• N/V POS tagging (specially for English)
David Moyes shares Manchester United fans' frustration
• Complex multiword extraction
Myeloid hepatosplenomegaly is an enlargement of liver and kidney due to myelofibrosis.
• Coordinations are difficult
Uncaria est une liane des jungles tropicales de l'Amérique du Sud et Centrale.
Aristotle was a Greek philosopher, a student of Plato and teacher of Alexander the Great.
• Citations and titles need to be treated differently
Anna Karenina is also mentioned in R. L. Stine's Goosebumps series Don't Go To Sleep.
• Plural coreferences are hard
When Carol helps Bob and Bob helps Carol, they can accomplish any task.
54. • The path descended abruptly
• The road runs along the coast for two hours
• The fence zigzags from the plateau to the valley
• The highway crawls through the city
• The road leads us to Bordeaux
• Need for “type coercion” to satisfy hidden frame
• highway is actually a path that “can be crawled”, therefore the crawling frame here is descriptive
of a state, not of an action
• fence is actually an object whose shape “can be followed by zigzaging”
• road is actually an object that “can be followed as an indication” to our destination
• sometimes an inversion of roles: the path descends because it can be descended
2. “in praesentia” semantics besides literal
interpretation
E.g. fictive motion and coercion (Talmy, Welty, Retoré)
55. adjective semantics
• Carmelo is a Sicilian surgeon
• Carmelo is an arsonist
• ⊨ Carmelo is a Sicilian arsonist
• Carmelo is a skilful surgeon
• ⊭ Carmelo is a skilful arsonist
• Carmelo is the alleged surgeon
• ⊭ Carmelo is the alleged arsonist
• ?⊨ Carmelo is a surgeon
• Carmelo is a fake surgeon
• ⊭ Carmelo is a fake arsonist
• ⊭ Carmelo is a surgeon
56. • How many frames? (FrameNet, VerbNet, etc. have a small
coverage), roles are often partly covered, mapping between frame
resources and linguistic constructions is seriously incomplete
• Interaction between in praesentia (traditional machine reading)
and in absentia (SW-machine reading) knowledge is complicated:
how about relevance, novelty, situatedness, etc.?
• Mario, please pass me the glass over there
• Mario, I feel sick … how about the meal we had yesterday?
• Mario, we are in last year’s situation
3. “in absentia” semantics: implicatures,
presuppositions, tacit knowledge, reference to
the physical world
57. • I saw the Coliseum in my tourist guide and wanted to go there
• artifact vs. place
• Actually relevant?
• Power of ambiguity (“systematic polysemy”)
• Minimal effort seems to count in human evolution of lexical knowledge, but
only if we can easily reconstruct the context (or frame, relation, ...)
• “The communicative function of ambiguity in language” (Piantadosi, Tilyb, Gibson,
@PLoS): ambiguity allows for greater ease of processing by permitting efficient
linguistic units to be re-used. “All efficient communication systems will be ambiguous,
assuming that context is informative about meaning”
• Also in science: inflammation has several interrelated meanings
Dot objects, co-predication
(Pustejovsky, Asher)
58. 4. higher-order phenomena: emergent frames, social
(and legal) norms, attitudes, argumentation, cultural
frames and narratives, discourse marks, text types
• Weak results for automatic extraction of discourse marks and their related semantics
• Attitude/argumentation lenses over basic semantics
• Bhatkal's father: I'm glad he has been arrested
• I disagree with the comments of reviewer 1, but reviewer 2 should provide a stronger
basis to his low rating
• Text types
• A cat is on the mat / A cat is a mammal
• Norms
• I should/feel obliged/want/obey/fear … it’s required/acceptable/convenient/proper/
suggested …
• Complex frames/narratives
• We need tax relief vs. Taxes are investments
62. Result in triples
People hope that the President will be condemned by the judges
Aldo Gangemi, Valentina Presutti, Diego Reforgiato Recupero.
Frame-based detection of opinion holders and topics: a model
and a tool. IEEE Computational Intelligence Magazine, 9(1), 2014
64. Approximating adjective
semantics
• New adjective ontology derived by reasoning on
top of an integrated resource including
(Onto)WordNet and FrameNet-RDF
• Four ontology design patterns for the four main
semantics identified
Adjective Semantics in Open Knowledge Extraction. A. Gangemi, A.G. Nuzzolese, V. Presutti and
D. Reforgiato, Formal Ontology in Information Systems Conference (FOIS2106), IOS Press, 2016.
65. Approximating adjective
semantics: patterns
• Base:
--> create taxonomy and intensional quality
:SkilfulSurgeon rdfs:subClassOf Surgeon .
:surgeon_1 a :SkilfulSurgeon .
:SkilfulSurgeon dul:hasQuality :Skilful .
• Extensional (Base + individual Quality):
--> create taxonomy and individual+intensional quality
:CanadianSurgeon rdfs:subClassOf :Surgeon .
:surgeon_1 a :CanadianSurgeon .
:surgeon_1 dul:hasQuality :Canadian .
:CanadianSurgeon dul:hasQuality :Canadian .
• Modal:
--> create association and intensional modality
:surgeon_1 a :AllegedSurgeon .
:AllegedSurgeon dul:associatedWith :Surgeon .
:AllegedSurgeon boxing:hasModality :Alleged .
• Privative:
--> create association and intensional quality
:surgeon_1 a :Fake_surgeon .
:Fake_surgeon dul:associatedWith :Surgeon .
:Fake_surgeon dul:hasQuality :Fake .
66. Approximating adjective semantics: example
The alleged doctor failed to transplant the fake organ
into the nice patient that borrowed a Canadian car
67. Passing the baton
• We have seen knowledge engineering on the SW as kind of
pattern science
• Reusable patterns
• Procedural practices
• Discoverable patterns
• Pattern-based formal knowledge extraction
• How logical and statistical techniques can be formally
hybridised, so leveraging the legacy of Pat Hayes and David
Mumford?
68. Other useful links
• FRED web application
• http://wit.istc.cnr.it/stlab-tools/fred/demo
• FRED API documentation
• http://wit.istc.cnr.it/stlab-tools/fred/api
• A FRED benchmark in N-Quads
• complete with annotations
• https://www.dropbox.com/s/q6b47dxmwyyseij/goldfrombenchmark.nq?dl=0
• only the semantic subgraph
• https://www.dropbox.com/s/p7w8nojb2g2yf8k/
goldfrombenchmark_semtriples.nq?dl=0