![Page 1: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/1.jpg)
Meaning on the WebAn Empirical Design Perspective
Aldo [email protected]
Semantic Technology LabInstitute for Cognitive Sciences and Technologies
National Research Council, Rome, ItalyWork described is by STLab people:
Francesco Draicchio, Alberto Musetti, Andrea Nuzzolese, Valentina PresuttiAlessandro Adamou, Eva Blomqvist, Enrico Daga
1
![Page 2: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/2.jpg)
What is this?
2
![Page 3: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/3.jpg)
Are these similar?
3
![Page 4: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/4.jpg)
What do you mean?• Mathieu did it slowly and deliberately, at
midnight, in the bathroom, with a knife
4
![Page 5: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/5.jpg)
Killing?
5
![Page 6: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/6.jpg)
Shaving?
6
![Page 7: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/7.jpg)
Hanging puppets?
7
![Page 8: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/8.jpg)
Actually ...• Mathieu buttered the toast slowly and
deliberately, at midnight, in the bathroom, with a knife
8
Donald Davidson: The Logical Form of Ac1on Sentences, 1967“the 'it' ... seems to refer to some en?ty”Davidson’s analysis started formal analysis of language in a modern way, and gave a founda?on to frame logics, which were the original use case for descrip?on logics ...That ‘it’ is key to meaning
![Page 9: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/9.jpg)
What is the key to access meaning?• When interpreting images? pattern recognition• When understanding text? parsing, resolution, expectations (background
knowledge), hypothesis formation• For querying databases? key discovery• For social data mashups? application design (e.g. FB)• For linked data mashups? sparql queries, ontologies• For event recognition, situation awareness? context ontologies, cqels queries• Such “keys” provide access by putting the pieces together. Can we make
ontology design as an empirical science of putting pieces of meaning together?
9
![Page 10: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/10.jpg)
Cognitive background
10
![Page 11: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/11.jpg)
Blink and “thin slicing”• Many organisms share the ability to gather a
snap judgment about a situation in a blink of an eye (cf. M. Gladwell, Blink)–making sense of situations based on thin slices of
experience: few color spots, a quick movement, a hat, the length of hair, a facial expression, the relative position of two persons, ...
• Positive and negative slicing–quick reaction and expectation building vs.
stereotypes and prejudices
11
![Page 12: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/12.jpg)
Blink and “thin slicing”• Many organisms share the ability to gather a
snap judgment about a situation in a blink of an eye (cf. M. Gladwell, Blink)–making sense of situations based on thin slices of
experience: few color spots, a quick movement, a hat, the length of hair, a facial expression, the relative position of two persons, ...
• Positive and negative slicing–quick reaction and expectation building vs.
stereotypes and prejudices
11
![Page 13: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/13.jpg)
Foreground and background• People tend to remember things because they
stick out from the background (“profiling”)– but what makes a background as such?
• Expectations create scenarios– even things that are not there become part of the
scenario if activated by an expectation• Cf. Gestalt psychology (Köhler, Langacker, etc.)
12
![Page 14: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/14.jpg)
Schema-based memory• People tend to remember items that fit into a
schema. – Things that are associated through some functional
similarity (cf. Gibson’s affordances)• Schemata seem to be learnt mostly inductively
–blocks world, repeated verbalization of invariant scenes, peek-a-boo, etc. Cf. Deb Roy’s TED talk
• Schema similar to (conceptual) frame, script, knowledge pattern, etc.
13
![Page 15: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/15.jpg)
Origin of modern frames and knowledge patterns
• «When one encounters a new situation (or makes a substantial change in one's view of the present problem) one selects from memory a structure called a Frame. This is a remembered framework to be adapted to fit reality by changing details as necessary … a frame is a data-structure for representing a stereotyped situation» (Minsky 1975)
• Frames, schemas, scripts … «These large-scale knowledge configurations supply top-down input for a wide range of communicative and interactive tasks … the availability of global patterns of knowledge cuts down on non-determinacy enough to offset idiosyncratic bottom-up input that might otherwise be confusing» (Beaugrande, 1980)
![Page 16: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/16.jpg)
How many frames?
• We (STLab) are collecting, reengineering, and aligning knowledge patterns from different knowledge formats into RDF and OWL–Web data: microformats, microdata, XML patterns–Linked data: induced schemas, data patterns–(Semantic web) ontologies: ontology design patterns,
extracted modules, query patterns–Linguistics: FrameNet and VerbNet frames, NLP-
extracted selectional restrictions, situations from parsed NL text
15
![Page 17: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/17.jpg)
Limited keys totext/discourse understanding
16
![Page 18: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/18.jpg)
What is a window?• (i) opening in a wall
– An opening, usually covered by one or more panes of clear glass, to allow light and air from outside to enter a building or vehicle. (Wiktionary)
• (ii) glass-filled frame fitting an opening in a wall– Welcome to Window World, America's Largest
Replacement Windows Company! (...) installs over 1 million replacement windows annually. (Ad)
• (iii) glass-filled frame– A window is a transparent or translucent opening in
a wall or door that allows the passage of light and, if not closed or sealed, air and sound. (Wikipedia)
• (iv) glass from glass-filled frame– A pane of glass in a window. (WordNet)
• (v) frame from glass-filled frame– A framework of wood or metal that contains a glass
windowpane and is built into a wall or roof to admit light or air. (WordNet) 17
![Page 19: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/19.jpg)
Genres of polysemy in WordNet• Adam’s apple (metaphor)
– thyroid cartilage_1 (dul:PhysicalObject)– crape jasmine_1 (dul:Organism)
• Bucket shop (diachronic metaphor)– bucket shop_2 (dul:PhysicalObject)
• “(formerly) a cheap saloon selling liquor by the bucket”
– bucket shop_1 (dul:Organization)• “an unethical or overly aggressive brokerage firm”
• Stadium (established metonymy, “dot object”)– stadium_1 (dul:PhysicalObject)
• “a large structure for open-air sports or entertainments”
– arena_4 (d0:Location)• “a playing field where sports events take place”
– do we need a relation between these senses, or a coarser concept? 18
![Page 20: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/20.jpg)
Dot objects and co-predication (Pustejovsky, Asher)
• This book is heavy but interesting– physical vs. information
• Lunch was delicious but took forever– food vs. event
• 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): 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 six interrelated meanings19
![Page 21: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/21.jpg)
“Fictive motion” (Talmy)• 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 Cercedilla• Need for “type coercion” to satisfy hidden frame
– highway is actually a path that “can be crawled”, therefore 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– Actually an inversion of roles: the path descends because it can be
descended: another version of systematic polysemy20
![Page 22: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/22.jpg)
Meaning as relation
21
![Page 23: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/23.jpg)
Meaning as relation• Event discovery and recognition
– { Water in pot ; pot on the hot stove ; egg in water } ∴ ???
• Meaning as a relational thing– Does “Egg” have a meaning independently of its relations? no, if meaning is what someone
does (or might do) with something?– cf. Bartlett, Davidson, Fillmore, Minsky, Schank, Brian Smith, Gibson, ...
• Dynamics (induction, abduction) of general and domain relations– Cook(Egg, Stove) as Absorb_heat(Entity, Heat_source) as Becoming(Entity, Cause)
21
![Page 24: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/24.jpg)
Meaning as relation• Event discovery and recognition
– { Water in pot ; pot on the hot stove ; egg in water } ∴ ???
• Meaning as a relational thing– Does “Egg” have a meaning independently of its relations? no, if meaning is what someone
does (or might do) with something?– cf. Bartlett, Davidson, Fillmore, Minsky, Schank, Brian Smith, Gibson, ...
• Dynamics (induction, abduction) of general and domain relations– Cook(Egg, Stove) as Absorb_heat(Entity, Heat_source) as Becoming(Entity, Cause)
21
FrameNet frameshave a par?al order
![Page 25: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/25.jpg)
Meaning as relation• Event discovery and recognition
– { Water in pot ; pot on the hot stove ; egg in water } ∴ ???
• Meaning as a relational thing– Does “Egg” have a meaning independently of its relations? no, if meaning is what someone
does (or might do) with something?– cf. Bartlett, Davidson, Fillmore, Minsky, Schank, Brian Smith, Gibson, ...
• Dynamics (induction, abduction) of general and domain relations– Cook(Egg, Stove) as Absorb_heat(Entity, Heat_source) as Becoming(Entity, Cause)
21
FrameNet frameshave a par?al order
![Page 26: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/26.jpg)
Limited keys tosocial tagging analysis
22
![Page 27: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/27.jpg)
Flickr, desire tag
23
![Page 28: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/28.jpg)
Flickr, desire tag
24
![Page 29: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/29.jpg)
Flickr, desire tag
25
![Page 30: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/30.jpg)
Similarly in other folksonomies
• like in FB, G+, etc.– like what? thing, comment to thing, content of
cited thing, implicit negative attitude to thing?• positive/negative polarity in sentiment
analysis– polarity of what? tweet, citation, irony, ...
26
![Page 31: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/31.jpg)
Limited keys tolinked data analysis
27
![Page 32: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/32.jpg)
28
Aggregated RDF data for “Barack
Obama” (sig.ma)
![Page 33: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/33.jpg)
What about the Knowledge Graph?
29
however, where are the IRIs? named en11es are only searchable within the Google engine, content is completely encrypted
![Page 34: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/34.jpg)
Ontologies disagree
30
Is that a problem?For many, yes
![Page 35: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/35.jpg)
schema.org• The use cases that motivated schema.org are
related to search engine requirements, probably to meet popularity and advertisement
• We received schemas from the “Sponsors”. As often happens, “sponsors” create meaning, because they have either authority or money
• Will ontologies be swallowed by the Sponsors?• Anyway, schemas from schema.org seem to
address keys more accurately, with some exceptions ...
31
![Page 36: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/36.jpg)
Pragmatic issue: we can communicate with landforms
32
![Page 37: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/37.jpg)
Pragmatic issue: we can communicate with landforms
32
![Page 38: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/38.jpg)
Pragmatic issue: we can communicate with landforms
32
![Page 39: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/39.jpg)
Pragmatic issue: we can communicate with landforms
32
![Page 40: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/40.jpg)
Pragmatic issue: we can communicate with landforms
32
![Page 41: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/41.jpg)
33
Application issue: bone pathologies, locations, functions are all literals
![Page 42: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/42.jpg)
33
Application issue: bone pathologies, locations, functions are all literals
![Page 43: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/43.jpg)
33
Application issue: bone pathologies, locations, functions are all literals
![Page 44: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/44.jpg)
33
Application issue: bone pathologies, locations, functions are all literals
![Page 45: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/45.jpg)
Creating keys for the Semantic Web
34
![Page 46: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/46.jpg)
Top-down: expertise patterns• 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?
35
![Page 47: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/47.jpg)
Layered pattern morphisms• A logical 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”
LogicalPaPern(MBox)
GenericContentPaPern (TBox)
SpecificContentPaPern (TBox)
DataPaPern (ABox)
exemplifiedAs morphedAs instan1atedAs Linguis?cPaPern
expressedAs
Logic Meaning Reference Expression
expressedAs
expressedAs
Abstrac1on
![Page 48: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/48.jpg)
Bottom-up: schema extraction (COLD2011)
37
![Page 49: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/49.jpg)
Results• A method for extracting the main knowledge components
of a LD dataset
mo:available_as
mo:format
mo:Track
mo:Playlist
mo:Record
mo:track
mo:Record
mo:trackmo:Track
foaf:maker
foaf:name
mo:MusicAr1st
dc:1tle
mo:available_asmo:Playlist
mo:Record mo:track mo:Track mo:available_as mo:Playlist dc:format rdfs:Literalmo:Signal mo:published_as mo:Track mo:available_as mo:Playlist dc:format rdfs:Literalmo:MusicArtist foaf:made mo:Record mo:available_as mo:Torrent dc:format rdfs:Literalmo:MusicArtist foaf:made mo:Record mo:available_as mo:ED2K dc:format rdfs:Literalmo:MusicArtist foaf:made mo:Record mo:available_as mo:Playlist dc:format rdfs:Literal
Path
Cluster of paths
Knowledge PaPern
![Page 50: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/50.jpg)
Path identification (length 3)mo:MusicAr?st
mo:Track
mo:Record
mo:Playlist
mo:Signal
rdfs:Literal
PREFIX mo : http://purl.org/ontology/mo/MusicArtist
rdfs:Resource
dc:1tle
mo:published_as
mo:recorded_as
(Jamendo)
foaf:Document
![Page 51: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/51.jpg)
Path identification (length 3)mo:MusicAr?st
mo:Track
mo:Record
mo:Playlist
mo:Signal
rdfs:Literal
PREFIX mo : http://purl.org/ontology/mo/MusicArtist
rdfs:Resource
dc:1tle
mo:published_as
mo:recorded_as
(Jamendo)
foaf:Document
Path ElementPosi?on 2
![Page 52: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/52.jpg)
Centrality (types)mo:MusicAr?st
mo:Track
mo:Record
mo:Playlist
mo:Signal
rdfs:Literal
PREFIX mo : http://purl.org/ontology/mo/MusicArtist
rdfs:Resource
(Jamendo)
foaf:Document
dc:1tle
mo:published_as
mo:track
mo:license
mo:track_number
mo:available_as
![Page 53: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/53.jpg)
Centrality (properties)mo:MusicAr?st
mo:Track
mo:Record
mo:Playlist
mo:Signal
rdfs:Literal
PREFIX mo : http://purl.org/ontology/mo/MusicArtist
rdfs:Resource
(Jamendo)
foaf:Document
dc:1tle
mo:published_as
mo:license
mo:track_number
mo:available_as
mo:recorded_as
![Page 54: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/54.jpg)
42
0 2 4 6 8 10 12
foaf:made foaf:maker
mo:available_as mo:published_as
mo:track mo:time
tags2:taggedWithTag
0 20000 40000 60000 80000 100000 120000 140000
mo:available_as tags2:taggedWithTag
mo:published_as mo:time mo:track
foaf:made foaf:maker
0 2 4 6 8 10 12
mo:Record
mo:Track
mo:MusicArtist
mo:Playlist
mo:Signal
time:Interval
mo:ED2K
mo:Torrent
tags2:Tag
mo:Lyrics
0 20000 40000 60000 80000 100000 120000
mo:Playlist
mo:Track
mo:Signal
time:Interval
mo:ED2K
mo:Torrent
tags2:Tag
mo:Lyrics
mo:Record
mo:MusicArtist
Centrality in Jamendo
frequency
betweenness
![Page 55: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/55.jpg)
Emerging Knowledge Patternmo:Track
mo:MusicAr.st
mo:Playlist
mo:Torrent
mo:ED2K
tags:Tag
mo:Record
foaf:maker
rdfs:Literal
dc:1tle
dc:datemo:image
dc:descrip1on
mo:track
tags:taggedWithTag
mo:available_as
mo:available_as
mo:available_as
![Page 56: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/56.jpg)
Bottom-up: Encyclopedic Knowledge Patterns (EKP) (ISWC2011)
• Improving knowledge exploration and summarization by:–Empirically discovering invariances in conceptual
organization of knowledge – encyclopedic knowledge patterns – from Wikipedia crowd-sourced page links
–Understanding the most intuitive way of selecting relevant entities used to describe a given entity
– Identifying the typical / atypical types of things that people use for describing other things
–Enabling serendipitous search
![Page 57: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/57.jpg)
Input data• Wikipedia page links generate 107.9M triples• Infobox-based triples are 13.6M, including data value triples (9.4M) • “Unmapped” object value triples are only 7% of page links
![Page 58: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/58.jpg)
Input data• Wikipedia page links generate 107.9M triples• Infobox-based triples are 13.6M, including data value triples (9.4M) • “Unmapped” object value triples are only 7% of page links
dbpo:MusicalArtist
dbpo:MusicalArtist dbpo:Organisation dbpo:Place
![Page 59: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/59.jpg)
Input data• Wikipedia page links generate 107.9M triples• Infobox-based triples are 13.6M, including data value triples (9.4M) • “Unmapped” object value triples are only 7% of page links
dbpo:MusicalArtistdbpo:MusicalArtist
dbpo:Organisation
dbpo:PlacelinksToMusicalArtist linksToPlace
linksToOrganisation
• Paths are used to discover Encyclopedic Knowledge Patterns– Such patterns should make it emerge the most typical types of things that the Wikipedia
crowd uses to describe a resource of a given type
![Page 60: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/60.jpg)
Input data• Wikipedia page links generate 107.9M triples• Infobox-based triples are 13.6M, including data value triples (9.4M) • “Unmapped” object value triples are only 7% of page links
dbpo:MusicalArtistdbpo:MusicalArtist
dbpo:Organisation
dbpo:PlacelinksToMusicalArtist linksToPlace
linksToOrganisation
• Paths are used to discover Encyclopedic Knowledge Patterns– Such patterns should make it emerge the most typical types of things that the Wikipedia
crowd uses to describe a resource of a given type
Path Pi,j= [Si, p, Oj]
![Page 61: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/61.jpg)
Encyclopedic Knowledge Patterns• An Encyclopedic Knowledge Pattern (EKP) is discovered from the
paths emerging from Wikipedia page link invariances• They are represented as OWL2 ontologies
![Page 62: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/62.jpg)
Paths and indicators• Emerging paths are stored in RDF according
to the “Knowledge Architecture” vocabulary–Cf. our COLD2011 paper “Extracting core
knowledge from linked data”• Paths and types are associated with a set of
indicators
![Page 63: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/63.jpg)
nRes(dbpo:MusicalArtist)
Chad_Smith
John_Lennon
Michael_Jackson
PREFIX dbpo : http://dbpedia.org/ontology/
Paul_McCartney
Jackie_Jacksonrdf:type
Anthony_Kiedis
dbpo:MusicalArtist
dbpo:MusicalArtist
rdf:type
rdf:type
dbpo:MusicalArtist
rdf:type
rdf:type
rdf:type
Number of resources having type dbpo:MusicalArtist
dbpo:MusicalArtist
![Page 64: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/64.jpg)
nSubjectRes(Pi,j)
Dave_Grohl
Foo Fighters
John_Lennon
Michael_Jackson
PREFIX dbpo : http://dbpedia.org/ontology/
Paul_McCartney
Jackson_5
Beatles
Jackie_Jackson
dbpo:MusicalArtist dbpo:Banddbpo:wikiPageWikiLinkSi Oj
Nirvana
![Page 65: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/65.jpg)
nSubjectRes(Pi,j)
Dave_Grohl
Foo Fighters
John_Lennon
Michael_Jackson
PREFIX dbpo : http://dbpedia.org/ontology/
Paul_McCartney
Jackson_5
Beatles
Jackie_Jackson
dbpo:MusicalArtist dbpo:Banddbpo:wikiPageWikiLinkSi Oj
Nirvana
Number of distinct resources that participate in a path as subjects
![Page 66: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/66.jpg)
pathPopularity(Pi,j,Si)
Dave_Grohl
Foo Fighters
John_Lennon
Michael_Jackson
Paul_McCartney
Jackson_5
Beatles
Jackie_Jackson
Nirvana
Madonna
PrinceCharlie_Parker Keith_Jarrett
nSubjectRes(Pi,j)/nRes(Si)
![Page 67: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/67.jpg)
Path Popularity distribution examplePath pathPopularity
[MusicFestival,Band] 82.33[MusicFestival,MusicalArtist] 74.17[MusicFestival,Country] 74.02[MusicFestival,MusicGenre] 72.81[MusicFestival,City] 38.37[MusicFestival,AdministrativeRegion] 32.78[MusicFestival,MusicFestival] 23.26[MusicFestival,Album] 18.13[MusicFestival,Film] 12.39[MusicFestival,Stadium] 9.52[MusicFestival,RadioStation] 9.52[MusicFestival,Single] 8.76[MusicFestival,Town] 8.61[MusicFestival,Magazine] 8.46[MusicFestival,Broadcast] 7.55[MusicFestival,Newspaper] 6.95[MusicFestival,TelevisionShow] 6.04[MusicFestival,University] 5.74[MusicFestival,Continent] 5.59[MusicFestival,Comedian] 5.29[MusicFestival,OfficeHolder] 4.98[MusicFestival,Island] 4.98
![Page 68: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/68.jpg)
Boundaries of EKPs• An EKP(Si) is a set of paths, such that
Pi,j ∈ EKP(Si) ! pathPopularity(Pi,j, Si) ≥ t
• t is a threshold, under which a path is not included in an EKP
• How to get a good value for t?
![Page 69: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/69.jpg)
Boundary inductionStep Description
1. For each path, calculate the path popularity
2. For each subject type, get the 40 top-ranked path popularity values*
3. Apply multiple correlation (Pearson ρ) between the paths of all subject types by rank, and check for homogeneity of ranks across subject types
4. For each of the 40 path popularity ranks, calculate its mean across all subject types
5. Apply k-means clustering on the 40 ranks
6. Decide threshold(s) based on k-means as well as other indicators (e.g. FrameNet roles distribution)
* 40 covers most “core” path popularity values, as well as many of the unusual ones.
.9
![Page 70: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/70.jpg)
k-means clustering on Path Popularity
Sample distribution of pathPopularity for DBpedia paths. The x-axis indicates how many paths (on average) are above a certain value t for pathPopularity
![Page 71: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/71.jpg)
k-means clustering on Path Popularity
1 big cluster (4-cluster) with ranks below 18.18%
Sample distribution of pathPopularity for DBpedia paths. The x-axis indicates how many paths (on average) are above a certain value t for pathPopularity
![Page 72: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/72.jpg)
k-means clustering on Path Popularity
1 big cluster (4-cluster) with ranks below 18.18%
3 small clusters with ranks above 22.67%
Sample distribution of pathPopularity for DBpedia paths. The x-axis indicates how many paths (on average) are above a certain value t for pathPopularity
![Page 73: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/73.jpg)
k-means clustering on Path Popularity
1 big cluster (4-cluster) with ranks below 18.18%
3 small clusters with ranks above 22.67%
Sample distribution of pathPopularity for DBpedia paths. The x-axis indicates how many paths (on average) are above a certain value t for pathPopularity
![Page 74: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/74.jpg)
k-means clustering on Path Popularity
1 big cluster (4-cluster) with ranks below 18.18%
3 small clusters with ranks above 22.67%
Sample distribution of pathPopularity for DBpedia paths. The x-axis indicates how many paths (on average) are above a certain value t for pathPopularity
1 alternative cluster (6-cluster) with ranks below 11.89%
![Page 75: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/75.jpg)
What is the “agreement” between DBpedia and our sample users?
Average multiple correlation (Spearman ρ) between users’ assigned scores, and
pathPopularityDBpedia based scoresSpearman ρ range: [-1,1] −1 = no agreement
+1 = complete agreement)
Multiple correlation coefficient (Spearman ρ) between users’s assigned score, and
pathPopularityDBpedia based score
![Page 76: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/76.jpg)
What is the “agreement” between DBpedia and our sample users?
Average multiple correlation (Spearman ρ) between users’ assigned scores, and
pathPopularityDBpedia based scoresSpearman ρ range: [-1,1] −1 = no agreement
+1 = complete agreement)
Multiple correlation coefficient (Spearman ρ) between users’s assigned score, and
pathPopularityDBpedia based score
Good correlation
Satisfactory precision
![Page 77: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/77.jpg)
What is the “agreement” between DBpedia and our sample users?
Average multiple correlation (Spearman ρ) between users’ assigned scores, and
pathPopularityDBpedia based scoresSpearman ρ range: [-1,1] −1 = no agreement
+1 = complete agreement)
Multiple correlation coefficient (Spearman ρ) between users’s assigned score, and
pathPopularityDBpedia based score
Good correlation
Satisfactory precision
Pi,j ∈ EKP (Si) ⇔pathPopularity(Pi,j, Si) ≥
11%
![Page 78: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/78.jpg)
Aemoo• http://aemoo.org exploratory search application based on
EKP
![Page 79: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/79.jpg)
Comparing entities of the same type
58
Nicolas Sarkozy Ronald Regan Angela MerkelBarack Obama Silvio Berlusconi
![Page 80: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/80.jpg)
Applying topic-sensitive EKP as lenses
59
![Page 81: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/81.jpg)
Limited keys totext/discourse analysis
60
![Page 82: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/82.jpg)
Ontology learning: what structures?
• State of art: what do we learn?– instances (NER): BarackObama– classes (sense tagging): Person, or even TelevisionActor– relations between instances: CabezaDeVaca departed Spain– axioms: mostly taxonomic or disjointness, some work also on
learning restrictions: TelevisionActor disjointWith TVSeries– entire ontologies, but only as collections of independently learnt
axioms
61
![Page 83: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/83.jpg)
Kinds of text analyses• Lead example:
–“In early 1527, Cabeza De Vaca departed Spain as the treasurer of the Narvaez royal expedition to occupy the mainland of North America. After landing near Tampa Bay, Florida on April 15, 1528, Cabeza De Vaca and three other men would be the only survivors of the expedition party of 600 men.”
62
![Page 84: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/84.jpg)
Shallow parsing (Alchemy)• Language
– english
• Person (1)
– the only survivors
• GeographicFeature (1)
– Tampa Bay
• Continent (1)
– North America
• Country (1)
– Spain
• StateOrCounty (1)
– Florida
• Concept Tags (8)
– United States
– Florida
– Gulf of Mexico
– North America
– Tampa, Florida
– Narváez expedition
– American Civil War
– Tampa Bay
• Category
– Culture & Politics (confidence: 0.6598)
Named en?ty recogni?on
Language recogni?on
Concept tagging
Subject classifica?on
Rela?on (ac?on) extrac?on
![Page 85: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/85.jpg)
Entity resolution (Wikifier)
64Wikipedia-‐based topic detec?onNamed en?ty resolu?on
![Page 86: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/86.jpg)
Multimedia enrichment (Zemanta)
65
Related images
Related news
Related links and geo-‐referencing
![Page 87: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/87.jpg)
Linked data positioning (RelFinder)
66
![Page 88: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/88.jpg)
Deep parsing• Usage of syntactic parse trees• Formal semantic interpretation on top of
syntax
67
![Page 89: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/89.jpg)
Categorial parsing
68
w(1, 1, 'In', 'in', 'IN', 'I-PP', 'O', '(S[X]/S[X])/NP').w(1, 2, 'early', 'early', 'JJ', 'I-NP', 'I-DAT', 'N/N').w(1, 3, '1527', '1527', 'CD', 'I-NP', 'I-DAT', 'N').w(1, 4, ',', ',', ',', 'O', 'I-DAT', ',').w(1, 5, 'Cabeza', 'Cabeza', 'NNP', 'I-NP', 'I-ORG', 'N/N').w(1, 6, 'De', 'De', 'NNP', 'I-NP', 'I-ORG', 'N/N').w(1, 7, 'Vaca', 'Vaca', 'NNP', 'I-NP', 'I-ORG', 'N').w(1, 8, 'departed', 'depart', 'VBD', 'I-VP', 'O', '((S[dcl]\NP)/PP)/NP').w(1, 9, 'Spain', 'Spain', 'NNP', 'I-NP', 'O', 'N').w(1, 10, 'as', 'as', 'IN', 'I-PP', 'O', 'PP/NP').w(1, 11, 'the', 'the', 'DT', 'I-NP', 'O', 'NP[nb]/N').w(1, 12, 'treasurer', 'treasurer', 'NN', 'I-NP', 'O', 'N').w(1, 13, 'of', 'of', 'IN', 'I-PP', 'O', '(NP\NP)/NP').w(1, 14, 'the', 'the', 'DT', 'I-NP', 'O', 'NP[nb]/N').w(1, 15, 'Narvaez', 'Narvaez', 'NNP', 'I-NP', 'I-ORG', 'N/N').w(1, 16, 'royal', 'royal', 'NN', 'I-NP', 'O', 'N/N').w(1, 17, 'expedition', 'expedition', 'NN', 'I-NP', 'O', 'N').w(1, 18, 'to', 'to', 'TO', 'I-VP', 'O', '(S[to]\NP)/(S[b]\NP)').w(1, 19, 'occupy', 'occupy', 'VB', 'I-VP', 'O', '(S[b]\NP)/NP').w(1, 20, 'the', 'the', 'DT', 'I-NP', 'O', 'NP[nb]/N').w(1, 21, 'mainland', 'mainland', 'NN', 'I-NP', 'O', 'N').w(1, 22, 'of', 'of', 'IN', 'I-PP', 'O', '(NP\NP)/NP').w(1, 23, 'North', 'North', 'NNP', 'I-NP', 'I-LOC', 'N/N').w(1, 24, 'America', 'America', 'NNP', 'I-NP', 'I-LOC', 'N').w(1, 25, '.', '.', '.', 'O', 'O', '.').w(1, 26, 'After', 'after', 'IN', 'I-PP', 'O', '(S[X]/S[X])/NP').w(1, 27, 'landing', 'landing', 'NN', 'I-NP', 'O', 'N').w(1, 28, 'near', 'near', 'IN', 'I-PP', 'O', '(NP\NP)/NP').w(1, 29, 'Tampa', 'Tampa', 'NNP', 'I-NP', 'I-LOC', 'N/N').w(1, 30, 'Bay', 'Bay', 'NNP', 'I-NP', 'I-LOC', 'N').w(1, 31, ',', ',', ',', 'O', 'O', ',').w(1, 32, 'Florida', 'Florida', 'NNP', 'I-NP', 'I-LOC', 'N').w(1, 33, 'on', 'on', 'IN', 'I-PP', 'O', '(NP\NP)/NP').w(1, 34, 'April', 'April', 'NNP', 'I-NP', 'I-DAT', 'N/N[num]').w(1, 35, '15', '15', 'CD', 'I-NP', 'I-DAT', 'N[num]').w(1, 36, ',', ',', ',', 'I-NP', 'I-DAT', ',').w(1, 37, '1528', '1528', 'CD', 'I-NP', 'I-DAT', 'N\N').w(1, 38, ',', ',', ',', 'O', 'O', ',').w(1, 39, 'Cabeza', 'Cabeza', 'NNP', 'I-NP', 'I-ORG', 'N/N').w(1, 40, 'De', 'De', 'NNP', 'I-NP', 'I-ORG', 'N/N').w(1, 41, 'Vaca', 'Vaca', 'NNP', 'I-NP', 'I-ORG', 'N').w(1, 42, 'and', 'and', 'CC', 'O', 'O', 'conj').w(1, 43, 'three', 'three', 'CD', 'I-NP', 'O', 'N/N').w(1, 44, 'other', 'other', 'JJ', 'I-NP', 'O', 'N/N').w(1, 45, 'men', 'man', 'NNS', 'I-NP', 'O', 'N').w(1, 46, 'would', 'would', 'MD', 'I-VP', 'O', '(S[dcl]\NP)/(S[b]\NP)').w(1, 47, 'be', 'be', 'VB', 'I-VP', 'O', '(S[b]\NP)/NP').w(1, 48, 'the', 'the', 'DT', 'I-NP', 'O', 'NP[nb]/N').w(1, 49, 'only', 'only', 'JJ', 'I-NP', 'O', 'N/N').w(1, 50, 'survivors', 'survivor', 'NNS', 'I-NP', 'O', 'N').w(1, 51, 'of', 'of', 'IN', 'I-PP', 'O', '(NP\NP)/NP').w(1, 52, 'the', 'the', 'DT', 'I-NP', 'O', 'NP[nb]/N').w(1, 53, 'expedition', 'expedition', 'NN', 'I-NP', 'O', 'N/N').w(1, 54, 'party', 'party', 'NN', 'I-NP', 'O', 'N').w(1, 55, 'of', 'of', 'IN', 'I-PP', 'O', '(NP\NP)/NP').w(1, 56, '600', '600', 'CD', 'I-NP', 'O', 'N/N').w(1, 57, 'men', 'man', 'NNS', 'I-NP', 'O', 'N').w(1, 58, '.', '.', '.', 'O', 'O', '.').
![Page 90: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/90.jpg)
Relation extraction with OIE• Cabeza De Vaca ___departed___Spain• 0.9059944442645228• In early 1527 , Cabeza De Vaca departed Spain as the treasurer of the Narvaez royal expedition to
occupy the mainland of North America .• IN JJ CD , NNP NNP NNP VBD NNP IN DT NN IN DT NNP JJ NN TO VB DT NN IN NNP NNP .• B-PP B-NP I-NP O B-NP I-NP I-NP B-VP B-NP B-PP B-NP I-NP I-NP I-NP I-NP I-NP I-NP B-VP I-
VP B-NP I-NP I-NP I-NP I-NP O• cabeza de vaca___depart___spain
• three other men___would be the only survivors of___the expedition party of 600 men• 0.36592485864619345• After landing near Tampa Bay , Florida on April 15 , 1528 , Cabeza De Vaca and three other men
would be the only survivors of the expedition party of 600 men .• IN NN IN NNP NNP , NNP IN NNP CD , CD , NNP NNP NNP CC CD JJ NNS MD VB DT JJ NNS
IN DT NN NN IN CD NNS .• B-PP B-NP B-PP B-NP I-NP O B-NP B-PP B-NP I-NP I-NP I-NP O B-NP I-NP I-NP O B-NP I-NP I-
NP B-VP I-VP B-NP I-NP I-NP I-NP I-NP I-NP I-NP I-NP I-NP I-NP O• # other men___be survivor of___the expedition party of # men
69
![Page 91: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/91.jpg)
Creating keys for NL
70
![Page 92: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/92.jpg)
DRT• Discourse Representation Theory
– Hans Kamp: “A theory of truth and semantic representation”, 1981• A sentence meaning is taken to be an update operation on a context• DRT represents “the discourse context” as a discourse representation
structure (or DRS). A DRS includes:– A set of referents: the entities which have been introduced into the
context– A set of conditions: the predicates which are known to hold of these
entities– Basically a fragment of FOL
71
![Page 93: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/93.jpg)
DRT notation
72
![Page 94: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/94.jpg)
Boxer• Implementation of computational semantics (J. Bos)
with DRT output and Davidsonian predicates: reification of n-ary relations– E.g. preparing a coffee: agent, instrument, mix, place, time,
method, ...
• Semantic role labelling with VerbNet or FrameNet roles
• Pragmatic grasp, with statistical NER and sense tagging, tense logic, co-reference, presupposition, sentence integration, entailment, ...
73
![Page 95: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/95.jpg)
DRT semantic parsing + semantic role labellling in Boxer
74
![Page 96: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/96.jpg)
Issues when porting (Boxer) DRT to RDF
• Discourse referent variables: implicit or explicit?• No terminology recognition/extraction• No term compositionality• No periphrastic relations for properties (e.g. survivorOf)• Redundant variables• Missing definitional pragmatics• Implicit local restrictions• Many types of redundant “boxing” for embedded propositions, non-
standard negation, etc.• How to map efficiently to RDF/OWL?
75
![Page 97: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/97.jpg)
Using FRED (EKAW2012)
76
http://wit.istc.cnr.it/stlab-tools/fred/
![Page 98: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/98.jpg)
FRED RDF graph output
77
![Page 99: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/99.jpg)
Another example
78
The New York Times reported that John McCarthy died. He invented the programming language LISP.
![Page 100: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/100.jpg)
Heuristics to map Boxer DRT to RDF (1/2)
• Default predicates – H_pred1: special vocabulary for defaults, e.g. boxer:Per rdf:type owl:Class– H_pred2: mappings to existing vocabularies, e.g. foaf:Person ; dul:associatedWith ; time:Interval
• Default roles (SRL binary predicates)– H_rol: VerbNet/FrameNet vocabularies, e.g. verbnet:agent rdf:type owl:ObjectProperty
• Domain predicates– H_dom: default namespace, customizable, e.g. domain:Expedition ; domain:of
• Discourse referent variables: implicit or explicit?– H_ref: only referents of predicates are materialized, e.g. domain:survivor_1 rdf:type
domain:Survivor ; depart_1 rdf:type domain:Depart
• No terminology recognition/extraction– H_term: co-referential predicate merging, e.g. domain:ExpeditionParty
• No term compositionality– H_termc: create taxonomies by “unmerging” predicates, e.g. domain:ExpeditionParty
rdfs:subClassOf domain:Party
• No periphrastic relations– H_peri: generate “webby” properties, e.g. domain:survivorOf rdf:type owl:ObjectProperty79
![Page 101: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/101.jpg)
• Redundant variables– H_red: unify variables based on local Unique Name Assumption
• Boolean constructs– H_boo: special relations between domain predicates or individuals, e.g. domain:man_1
owl:differentFrom domain:man_2
• Propositions as arguments– H_pro: special relation between events, e.g. domain:report_1 vn:theme domain:depart_1
• Missing definitional pragmatics– H_def: bypassing discourse referents and forcing universal quantification, e.g.
domain:WindInstrument rdfs:subClassOf domain:MusicalInstrument
• Implicit local restrictions (optional)– H_res: inducing anonymous classes, e.g. domain:WindInstrument rdfs:subClassOf (locationOf
some domain:Contain)
80
Heuristics to map Boxer DRT to RDF (2/2)
![Page 102: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/102.jpg)
Wikipedia typing• Typing Wikipedia entities is not easy• A lot of resources, limited alignment, limited
coverage, different granularity• We realized a fresh approach by
– extracting NL definitions– producing RDF with FRED– refactoring FRED output to distill types– linking to DBpedia entities– linking to WordNet 3.0– linking to SuperSenses and DOLCE+DnS (DUL)
81
![Page 103: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/103.jpg)
Tìpalo: a FRED app
82
http://wit.istc.cnr.it/stlab-tools/tipalo/
![Page 104: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/104.jpg)
Definition of chaise longue
83
A chaise longue is an upholstered sofa in the shape of a chair that is long enough to support the legs
![Page 105: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/105.jpg)
Conclusions• Cognitive science is quite explicit on what meaning is
for humans: an activity of “framing reality for a purpose”
• Frames can be keys to that relational meaning• The Semantic Web is now growing a lot of data: our
tools are trying to make sense of them by using appropriate keys
• Empirical extraction and discovery of frames/knowledge patterns is feasible
• But let’s join forces: meaning is what we do, and should be shared
84
![Page 106: Aldo Gangemi - Meaning on the Web: An Empirical Design Perspective](https://reader036.vdocument.in/reader036/viewer/2022081603/558dfd151a28abba0d8b45ce/html5/thumbnails/106.jpg)
References• Alchemy (shallow parsing): http://www.alchemyapi.com/api/demo.html
• Wikifier (entity resolution): http://wit.istc.cnr.it/stlab-tools/wikifier
• Zemanta (multimedia enrichment): http://www.zemanta.com/demo/
• RelFinder (linked data visualization): http://www.visualdataweb.org/relfinder/demo.swf
• ReVerb (relation extraction): http://openie.cs.washington.edu/
• C&C (categorial grammar): http://svn.ask.it.usyd.edu.au/trac/candc/wiki/Demo
• Boxer (DRT deep parsing): http://svn.ask.it.usyd.edu.au/trac/candc/wiki/boxer
• FRED (DRT to RDF): http://wit.istc.cnr.it/stlab-tools/fred/
• Tìpalo (Wikipedia definitions in RDF): http://wit.istc.cnr.it/stlab-tools/tipalo
• Aemoo (serendipitous search): http://aemoo.org/
• ontologydesignpatterns.org portal: http://www.ontologydesignpatterns.org
• Talmy’s fictive motion: http://en.wikipedia.org/wiki/Fictive_motion
• Pustejovsky’ dot objects: http://pages.cs.brandeis.edu/~jamesp/publications.php
• Knowledge Architecture paper: http://ceur-ws.org/Vol-782/PresuttiEtAl_COLD2011.pdf
• FRED paper: http://ekaw2012.ekaw.org/node/137
• EKP paper: http://www.stlab.istc.cnr.it/documents/papers/wikilinkpatterns.pdf 85