2 notions of meaning
What formal semantics prescribes
What people do with it in practice
What is Empirial Semantics?
The empirical (i.e., non-analytic) analysis of meaning.
(We still use model theory and other
formalisms in order to describe the outcomes of
our analyses, but we do not use formalisms in order
to prescribe what a given expressions ought to
Why is Empirical Semantics needed? (1/2)
Some aspects of meaning cannot be captured by
formal meaning, but we still want to study them.
(We must observe these non-formal aspects of meaning
Formal semantics cannot capture all aspects of meaning
id:store def:sells id:tent.
id:tent def:costs "¥150,000".
id:tent rdf:type id:Product.
fy:aHup pe:ko9sap_ fy:jufn12.
fy:jufn12 pe:oao9_ "Ufou".
fy:jufn12 rdf:type fyufnt:tmffqt.
Graphs G₁ and G₂ are true in the same models.
In the early days of the Semantic Web (2003) the
non-formal aspects of meaning were actively
“An RDF graph may contain "defining information" that is
opaque to logical reasoners. This information may be
used by human interpreters of RDF information.”
“Human publishers of RDF content commit themselves to
the mechanically-inferred social obligations.”
“The meaning of an RDF document includes the social
meaning, the formal meaning, and the social meaning of
the formal entailments.”
Why is Empirical Semantics needed? (2/2)
Some aspects of meaning could (theoretically)
have been captured by formal meaning, but are observed
to not be captured as such in common practice.
(We must observe what ‘common practice’ is
Formally incorrect, but not meaningless
Empirical research fields require infra
Like other empirical research fields, Empirical Semantics requires a serious investment in infrastructure.
LOD Observatories are needed to observe and analyse the large-scale use of Knowledge Graphs in practice.
“Anyone can say anything about anything.”
AAA adapted for identity:
Anyone can say that anything is identical to anything
(and they do).
$$a = b \leftrightarrow (\forall \phi \in \Psi)(\phi(a) = \phi(b))$$
Pragmatics of owl:sameAs
Relatedness cannot replace identity
‘Barack Obama’ in LOD
But are these links correct?
Cluster detection for ‘Barack Obama’
Empirical Semantics Approach
Take a meta-assertion from Analytic Semantics and
evaluate it as an empirical hypothesis.
Our semantic meta-assertion / hypothesis for naming
“Names are chosen arbitrarily and have no meaning.”
Names on the Web
Quantifying the meaning of names
Mutual Information = encode(FORMAL_MEANING) +
encode(FORMAL_MEANING + NAMES)
- Names do not encode predicate information.
- Names do not encode type information.
Evaluated over ≥600,000 datasets
- Reproducible research
L. Rietveld, W. Beek & S. Schlobach, 2015.
“LOD Lab: Experiments at LOD Scale”, ISWC 2015.
Best Paper Award.
- Large-scale data cleaning
W. Beek, F. Ilievski, J. Debattista, S. Schlobach
& J. Wielemaker, “Literally better: Analyzing
and Improving the Quality of Literals”, Semantic
Web Journal 2017.
- Semantic search engines
F. Ilievski, W. Beek, M. Van Erp, L. Rietveld
& S. Schlobach, “LOTUS: Adaptive Text Search
for Big Linked Data”, ESWC 2016. Best LOD
- Large-scale querying
J. Fernández, W. Beek, M. Martínez-Prieto &
M. Arias, “LOD-a-lot: A Queryable Dump of the LOD
Cloud”, ISWC 2017.
W. Beek, J. Fernández & R. Verborgh,
“LOD-a-lot: A Single-file Enabler for Data
Science”, 13th Int. Conf. on Semantic Systems
W. Beek, L. Rietveld, S. Schlobach & F. Van
Harmelen, “LOD Laundromat: Why the Semantic Web
Needs Centralization (Even If We Don't Like It)”,
IEEE Internet Computing 2016.
L. Rietveld, R. Verborgh, W. Beek, M. Vander Sande
& S. Schlobach. 2015. “Linked
Data-as-a-Service: The Semantic Web Redeployed”,
- Erroneous link detection
W. Beek, J. Raad, J. Wielemaker & F. van
Harmelen “sameAs.cc: The Closure of 500M
owl:sameAs Statements”, ESWC 2018. Best
Resource Paper Award.
J. Raad, W. Beek, F. Van Harmelen, N. Pernelle
& F. Saïs, “Detecting Erroneous Identity Links
on the Web using Network Metrics”, ISWC 2018.