Framester and WFD

Word Frame Disambiguation:
Evaluating Linguistic Linked
Data on Frame Detection
Mehwish Alam1, Aldo Gangemi1,2, Valentina Presutti2
1LIPN, Paris Nord University, CNRS UMR7030, France
2Semantic Technology Lab, ISTC-CNR, Rome, Italy

Frames as eventuality
schemas
• Prepare_coffee(x,y)
• events as relations with ﬁxed arity
• Prepare_coffee(x,y,…)
• … adding multigrade arity (coffee mix, machine, time, recipe, …)
• Prepare_coffee(e,x,y,…)
• … adding reiﬁed eventualities [a.k.a. Neo-Davidsonian events]
• Prepare_coffee(e,x,y,…) ∧ agent(e,x) ∧ theme(e,y) ∧ …
• … adding semantic roles (agent, theme, time, location, …)
• Prepare_coffee(e,x,y,…) ∧ agent(e,x) ∧ theme(e,y) ∧ … ∧ Person(x) ∧ Beverage(y) ∧ …
• … adding semantic types (Person, Beverage, Coffee mix, Machine type, …)

How to detect frames?
• From:
• Linguistic structures (Valentina prepared a barley coffee)
• Relational tables, RDF datasets, OWL classes
(:BarleyCoffeePreparation :hasCook :Valentina ; :hasMaterial :myOrganicBarley .)
• XML stylesheets, templates, Web pages
• JSON microdata, infoboxes
• Requirements
• Using:
• Words (evocation: Valentina, prepare, barley, coffee)
• Word Senses, Synsets, Classes, Properties (predicates as unary or binary projections of frames:
Person, Activity, Cereal, Drink, agent, theme, ingredient)
• Entities (individuals: occurrences of unary projections: Valentina)
• Facts (assertions: occurrences of binary projections: prepares(Valentina, barley coffee))

%%% _______________________ ____________
%%% |x0 | |x1 x2 x3 |
%%% |.......................| |............|
%%% (|named(x0,valentina,per)|A|prepare(x3) |)
%%% |_______________________| |barley(x2) |
%%% |nn(x2,x1) |
%%% |coffee(x1) |
%%% |Agent(x3,x0)|
%%% |Theme(x3,x1)|
%%% |____________|
FRED+VerbNet+NER
FRED+FrameNet+NER
FRED-FrameNet+NER+UKB/WordNet
Boxer
ARK+Semafor

%%% _______________________ ____________
%%% |x0 | |x1 x2 x3 |
%%% |.......................| |............|
%%% (|named(x0,valentina,per)|A|prepare(x3) |)
%%% |_______________________| |barley(x2) |
%%% |nn(x2,x1) |
%%% |coffee(x1) |
%%% |Agent(x3,x0)|
%%% |Theme(x3,x1)|
%%% |____________|
framester:Food
fschema:unaryProjectionOf
frole:agent
frole:product
fschema:subsumedunder

Framester
A semiotic hub for knowledge graph interoperability
?

dataset nodes
blue: role-oriented lexical resources
purple: emotion-oriented lexical resources
red: fact-oriented data
green: wordnet-like lexical resources
yellow: ontology schemas
grey: topic models
dotted line: existing RDF data
continuous line: newly created RDF data
Originally, not many RDF datasets
linked in the word-lexicon-data space
arrows
orange: Framester links
black dotted: previous links

dataset nodes
red: fact-oriented data
grey: topic models
We added more RDF datasets linked in
the word-lexicon-data space
arrows

dataset nodes
orange: fact-oriented data
grey: topic models
arrows
We added many new
links so creating a
new formal resource
in the word-lexicon-
data space

Sample triples
• wn30instances:synset-anti-G_suit-noun-1
wn30schema:containsWordSense wn30instances:wordsense-
anti-G_suit-noun-1 , wn30instances:wordsense-G_suit-
noun-1 ; wn30schema:gloss “worn by fliers and
astronauts to counteract the forces of gravity and
acceleration” .
own2dul:proxhyp wn30instances:synset-pressure_suit-
noun-1 ; own2dul:hyp wn30instances:synset-
consumer_goods-noun-1 ; own2dul:d0
dul:PhysicalObject .
• wn30instances:synset-anti-G_suit-noun-1 a
fschema:SynsetFrame ; fschema:unaryProjectionOf
frame:Clothing , frame:Artifact , frame:Wearing ,
frame:Dressing .
wn30
own
framester

BabelNet2Framester
• bn:s00004603n lemon:isReferenceOf
bn:G_suit_EN/s00004603n .
• bn:G_suit_EN/s00004603n owl:sameAs
wn30instances:wordsense-G_suit-noun-1 .
• bn:s00004603n fschema:isUnaryProjectionOf
frame:Clothing , … , … .

DBpedia to Framester
• dbr:John_Holmes_(actor) a wn30instances:synset-actor-noun-1 .
• dbr:John_Holmes_(actor) fschema:hasRoleIn frame:Performers .
• dbr:John_Holmes_(rugby_league) a wn30instances:synset-player-
noun-1 .
• dbr:John_Holmes_(rugby_league) fschema:hasRoleIn
frame:Competition , frame:Participation .

Emo to Framester: SWN
swn:negScore "0" ; swn:posScore "0" .
• wn30instances:synset-coffee_fungus-noun-1
swn:negScore "0.375" ; swn:posScore "0" .

Framester semantics 1/3
• A frame is deﬁned as a multigrade predicate 𝜙(e,x1, ..., xn), where
𝜙 is a ﬁrst-order relation, e is a (neo-Davidsonian) variable for any
eventuality or state of affairs described by the frame, and xi is a
variable for any argument place. Interpretation of predicates is
made on a domain ∆
I
of
• D&S-style Punning
• 𝜙
I
⊆ dands:Situation
I
• 𝜙 ∈ fschema:Frame
I
(⊆ dands:Description
I
)
• Actual frame occurrences
• s ∈ fschema:Situation
I
, 𝜙
I

• Projections
• A semantic role is a internal binary projection rol(e,xi)
of a frame 𝜙, so that rol(e,xi) → 𝜙(e,x1, …,xn), i≥1≤n
• A co-participation relation is an external binary
projection cop(xj,xk) of a frame 𝜙, so that cop(xj,xk) →
𝜙(e,x1, …,xn), j≥1≤n , k≥1≤n
• A selectional restriction or semantic type is a unary
projection typ(xm) of a frame 𝜙, so that typ(xm) →
𝜙(e,x1, …,xn), m≥1≤n

• Individuals and words
• A (non-situational) individual entity ent has a role in a
possible occurrence of a frame 𝜙 when ent ∈ typI
, i.e.
when it is an instance of a type compatible (or coerced) as
a unary projection of 𝜙
• An individual tuple is a possible occurrence of a frame 𝜙
when <x,y> ∈ rolI
, or <x,y> ∈ copI
, i.e. when it is a
instance of a property compatible (or coerced) as a binary
projection of 𝜙
• A word is an evocation of a frame 𝜙 when it can be
disambiguated to a frame or one of its projections

Consequences
• WordNet synsets are unary projections of frames (synset-based frames)
• WordNet word senses are unary projections of lexical units (sense-based frames)
• WordNet “tropes” are binary projections of implicit synset-based frames
• VerbNet verb (sub-)classes are frames
• VerbNet verb class members are sense-based frames
• LD properties are binary projections of frames (either internal or external)
• LD classes are either (candidate) frames or unary projections of frames
• LD regular individuals are instances of unary projections of frames (role players in an external
data frame)
• LD qua-individuals (e.g. DBpedia career stations) are instances of unary projections of a
speciﬁc frame
• LD assertions are instances of binary projections of (?external) frames

Achievements
• more than 40 million triples including new LOD versions of many, linguistic/factual resources,
and links among them, and to Framester
• formal schema interoperability across datasets
• full revision of WordNet-FrameNet mappings
• large extension of frame coverage
• frame annotations for any kind of entity
• full mapping of local (frame-dependent), and global roles from multiple resources
• new semantic role taxonomy from localised roles way up to abstract roles and dependencies
• alignment of frames, roles and types to foundational ontologies
• new frame relations discovered based on mappings and inferences
• Word Frame Disambiguation service

Consequent issues
• Many wrong mappings e.g. in FrameBase-WordNet
• Many inaccurate subsumptions and cycles in FrameNet
frame elements because of heterogeneous inheritance/
causal semantics
• Other mixed errors in FrameNet, e.g. when composing
formal assumptions from frame/role taxonomies
• Errors in stand-off WordNet ﬁles (specially with
teleological and derivational morpho-semantics datasets)
• …

framester:Clothing
frole:agent,
frole:manner, frole:material,…
wn:synset-anti-G_suit-noun-1
fschema:unaryProjectionOf
fschema:binaryProjectionOf
dul:PhysicalObject
rdfs:subClassOf
framestersyn:anti-G_suit.n.1
fe:Wearer, fe:Style,
fe:Material …
fschema:subsumedUnder
fschema:subsumedUnder
dbr:G-suit
owl:sameAs
bn:s00004603n
owl:sameAs

Links
• Framester GitHub page
• https://github.com/framester/
Framester/wiki/Framester-
Documentation
• Endpoint
• http://etna.istc.cnr.it/framester/sparql
• WFD
• http://lipn.univ-paris13.fr/framester/
en/wfd/

R&D
• Word Frame Disambiguation
• Frame vectors and frame topic models (frame2vec for deep learning)
• OKE extensions (cf. FRED)
• Frame clustering and complex frame discovery
• Sentence frame ﬁngerprinting (valence patterns)
• Automated matching between semantic roles
• Automated matching between roles and LOD properties
• Overlap matching between frames and LOD classes
• Assisted eXtreme Design (ODP semantic search)
• …
(✔)
(✔)
(✔)
✔
✔

Conclusions
• A new large resource in LOD, linking linguistic and
factual knowledge with a frame-oriented semantics,
expressible in OWL
• Evaluation wrt frame detection proves increase of
recall and state-of-the-art precision
• A lot of research themes by applying links and
shared semantics: valence patterns, clustering,
embeddings, interoperability

Related publications: Framester
and frame semantics
• A. Gangemi, M. Alam, L. Asprino, V. Presutti, D.R.
Recupero. 2016. Framester: A Wide Coverage
Linguistic Linked Data Hub. EKAW
• Aldo Gangemi, 2010. What’s in a Schema?,
Ontology and the Lexicon, Cambridge University
Press
• Charles J Fillmore. 1976. Frame semantics and the
nature of language. Annals of the New York
Academy of Sciences

Related publications:
Linguistic resources
• Maddalen Lopez de Lacalle, Egoitz Laparra, and German Rigau. 2014. Predicate Matrix: extending
SemLink through WordNet mappings. LREC
• Antoine Zimmermann, Christophe Gravier, Julien Subercaze, and Quentin Cruzille. 2013. Nell2RDF:
Read the Web, and Turn it into RDF. KNOW@LOD, CEUR
• Montse Cuadros, Llúıs Padró, German Rigau. 2012. Highlighting relevant concepts from topic
signatures. LREC
• Roberto Navigli and Simone Paolo Ponzetto. 2012. BabelNet: The Automatic Construction, Evaluation
and Application of a Wide-Coverage Multi-lingual Semantic Network. Artiﬁcial Intelligence
• Andrew Carlson, Justin Betteridge, Bryan Kisiel, Burr Settles, Estevam R Hruschka Jr, and Tom M
Mitchell. 2010. Toward an architecture for never-ending language learning. AAAI
• Martha Palmer. 2009. Semlink: Linking Prop-Bank, VerbNet and FrameNet. GenLex-09
• Karin Kipper Schuler. 2005. Verbnet: A Broad-coverage, Comprehensive Verb Lexicon. Ph.D. thesis
• Christiane Fellbaum, editor. 1998. WordNet: an electronic lexical database, MIT Press
• Collin F. Baker, Charles J. Fillmore, and John B. Lowe. 1998. The Berkeley FrameNet Project.
COLING

Related publications: Linked
data resources
• Linguistic linked data resources
• Antoine Zimmermann, Christophe Gravier, Julien Subercaze, and Quentin Cruzille. 2013.
Nell2RDF: Read the Web, and Turn it into RDF. KNOW@LOD
• Andrea Giovanni Nuzzolese, Aldo Gangemi, and Valentina Presutti. 2011. Gathering lexical
linked data and knowledge patterns from FrameNet. KCAP
• Mark Van Assem, Aldo Gangemi, and Guus Schreiber. 2006. Conversion of WordNet to a
standard RDF/OWL representation. LREC
• Aldo Gangemi, Roberto Navigli, and Paola Velardi. 2003. The OntoWordNet project:
Extension and axiomatization of conceptual relations in Wordnet. ODBASE
• Factual inked data resources
• Jens Lehmann, Chris Bizer, Georgi Kobilarov, Sören Auer, Christian Becker, Richard
Cyganiak, and Sebastian Hellmann. 2009. DBpedia - A Crystallization Point for the Web of
Data. Journal of Web Semantics
• Johannes Hoffart, Fabian M Suchanek, Klaus Berberich, and Gerhard Weikum. 2013. Yago2:
A spatially and temporally enhanced knowledge base from wikipedia. Artiﬁcial Intelligence

Related publications: Tools
• Aldo Gangemi, Valentina Presutti, Diego Reforgiato
Recupero, Andrea Giovanni Nuzzolese, Francesco
Draicchio, and Misael Mongiovi. 2016. Semantic
Web Machine Reading with FRED. Semantic Web
• Dipanjan Das, Desai Chen, André F. T. Martins,
Nathan Schneider, and Noah A. Smith. 2014.
Frame-semantic parsing. Computational Linguistics

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