Framester: A Wide Coverage Linguistic Linked Data Hub

Framester: A Wide Coverage Linguistic Linked Data Hub.
Aldo Gangemi1
, Mehwish Alam1
, Luigi Asprino2,3
, Valentina Presutti3
, Diego
Reforgiato Recupero4
1. Universite Paris 13, Paris, France,
2. University of Bologna, Bologna, Italy
3. National Research Council (CNR), Rome, Italy
4. University of Cagliari, Cagliari, Italy
23rd
November 2016
International Conference on Knowledge Engineering and Knowledge Management, 2016
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Linguistic Linked Data (LLD) Framester Semantics Resource Generation Experimentation Conclusion
Existing State of LLD
Figure: Current state of Linguistic Linked Data and connections to other resources. Blue, red,
green and yellow color represent role-oriented lexical resources, fact-oriented data, wordnet-like
lexical resources and ontology schemas respectively.
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Framester - Linguistic Linked Data Hub
Figure: Framester Cloud. Red color represents the main hub i.e., Framester, Purple represents
the links to data sets for Sentiment Analysis. Black and orange arrows represent the existing and
Framester speciﬁc links respectively.
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FrameNet
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FrameNet
a
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Frames as Eventuality Schema
Hagrid rolled up a note
rollpHagrid, noteq
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rollpHagrid, noteq
Hagrid rolled up a note for Harry in Hogwarts
rollpHagrid, note, Harry, Hogwartsq
note: ambiguity in the arguments of predicate i.e., Harry is a person and Hogwarts is a location
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rollpHagrid, noteq
adding eventualities (Neo Davidsonian events)
rollpe, Hagrid, note, Harry, Hogwartsq
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rollpHagrid, noteq
adding semantic roles
rollpe, Hagrid, note, Harry, Hogwartsq ^ agentpe, Hagridq ^ themepe, noteq ^
recipientpe, Harryq ^ locationpe, Hogwartsq
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rollpHagrid, noteq
adding semantic roles
recipientpe, Harryq ^ locationpe, Hogwartsq
adding semantic types
recipientpe, Harryq ^ locationpe, Hogwartsq ^ PersonpHagridq...
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N-ary Relations in RDF
Original RDF Triple : e1 p e2
e1 e2
p
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Triple with reiﬁed eventuality:
e rdf:subject e_1 .
e rdf:predicate p .
e rdf:object e_2 .
e1 e2
e
p
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Triple with reiﬁed eventuality:
e rdf:subject e_1 .
e rdf:predicate p .
e rdf:object e_2 .
e1 e2
e
p
event type Reshaping .
event agent Hagrid .
event patient note .
event recipient Harry .
event location Hogwarts .
Reshaping
Hagrid
event note
Harry
Hogwarts
type
agent
patient
recipient
location
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Framester Schema
Situation FrameOccurence Framester Role
Description FrameClass FrameProjection R1
r1.f2
r2.f1 f1 r1.f1
f2 r3.f1
hasFrameProj.
subClassOf
occurrenceOf
subClassOf
inheritsFrom
subsumedUnder+
frame instance
role instance
optional
subsumedUnder
necessary
external
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Framester Frames Representation
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Improving FrameNet Coverage
WordNet/BabelNet-FrameNet Extensions
FrameNet Original Mappings (Proﬁle-F)
Framester Base (Proﬁle-B)
eXtended WordFrameNet [de Lacalle et al., 2014]
FrameBase [Rouces et al., 2015]
WN/BNSynset FrameNet
eXtended WordFrameNet
FrameBase
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DirectX (Proﬁle-D)
Synset Synset Synset
WN/BN Synset FrameNet
Synset Synset Synset
FrameBase
partainym Instance verb-group
participle hyponym adj-sim
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DirectX (Proﬁle-D)
TransX (Proﬁle-T)
Sysnset Sysnset Sysnset
WN/BN Synset FrameNet
Synset Sysnset Sysnset
Sysnset
FrameBase
partainym Instance verb-group
participle hyponym adj-sim
hyponym
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Links to Other Resources
WordNet Synset FrameNet
Resource URI/OWL-Class
skos:closeMatch
some-relation
DOLCE-Zero [Nuzzolese et al., 2012]
[ a framenet:fnwnd0Detour ;
framenet:forSynset wn30instances:synset-fireplace-noun-1 ;
framenet:hasFoundational d0:Location ;
framenet:onFrame frame:Architectural_part ] .
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Word Frame Disambiguation
Framework for Frame Detection.
Tokenisation, POS tagging, lemmatization, word sense disambiguation, and frame
detection by detour.
WSD algorithms:
Babelfy [Moro et al., 2014]
UKB [Agirre and Soroa, 2009]
Mapping between word senses and are matched against Word sense to Frame
alignment based on 4 proﬁles.
Example
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Word Frame Disambiguation
Framework for Frame Detection1
.
Tokenisation, POS tagging, lemmatization, word sense disambiguation, and frame
detection by detour.
WSD algorithms:
Babelfy [Moro et al., 2014]
UKB [Agirre and Soroa, 2009]
Mapping between word senses and are matched against Word sense to Frame
alignment based on 4 proﬁles.
1
http://lipn.univ-paris13.fr/framester/
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Experiment#1: FrameNet Corpus
WFD-API was used for evaluation purposes.
FrameNet annotated corpus v1.5 (gold standard)
78 documents with 170,000 manually annotated sentences,
UKB Babelfy
Framester Profiles Recall Precision F1 New Annotations Recall Precision F1 New Annotations
eXtended WFN 0.511 0.810 0.627 832 0.580 0.820 0.680 8129
FrameBase 0.719 0.714 0.716 1132 0.621 0.71 0.661 11035
Profile-F 0.688 0.777 0.702 1148 0.673 0.749 0.704 10962
Profile-B 0.671 0.799 0.729 1251 0.662 0.780 0.715 11661
Profile-D 0.750 0.641 0.690 1929 0.790 0.569 0.660 20382
Profile-T 0.860 0.520 0.648 2728 0.870 0.444 0.588 26108
Table: Results
Recall Precision F1 ´ Measure New Annotations
Semafor 0.76 0.96 0.85 16520
Table: Results for the baseline (Semafor).
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Experiment#2: Independent Corpus
Independent Corpus of 100 heterogeneous texts taken from New York Times news,
tweets, Wikipedia definitions, and scientific articles.
annotation using Framester profiles and semafor.
2 experts judged the correctness of the detected frames and missing detection
Judgements: Valid, Metaphorical2
, or Invalid
inter-rater agreement using weighted Cohen’s K (WKAPPA) (value 0.532)
Third expert to take decisions when the two raters had different opinions.
Precision Recall F1
eXtended WFN 0.770 0.277 0.523
FrameBase 0.703 0.359 0.531
Profile-B 0.776 0.366 0.571
Profile-D 0.705 0.622 0.663
Profile-T 0.644 0.781 0.713
Profile-F 0.750 0.377 0.564
Semafor 0.794 0.334 0.564
Table: Results
2
Frame Travel in Our love traveled distances
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Conclusion
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
new semantic role taxonomy from localised roles way up to abstract roles and
dependencies
alignment of frames, roles and types to foundational ontologies
Word Frame Disambiguation service
Ongoing Work:
Frame vectors (frame2vec).
Frame clustering and complex frame discovery.
Semantic Relatedness between Frames.
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References I
Agirre, E. and Soroa, A. (2009).
Personalizing PageRank for Word Sense Disambiguation.
In Lascarides, A., Gardent, C., and Nivre, J., editors, EACL 2009, 12th Conference
of the European Chapter of the Association for Computational Linguistics,
Proceedings of the Conference, Athens, Greece, March 30 - April 3, 2009, pages
33–41. The Association for Computer Linguistics.
Baccianella, S., Esuli, A., and Sebastiani, F. (2010).
SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and
Opinion Mining.
In Calzolari, N., Choukri, K., Maegaard, B., Mariani, J., Odijk, J., Piperidis, S.,
Rosner, M., and Tapias, D., editors, Proceedings of the International Conference on
Language Resources and Evaluation, LREC 2010, 17-23 May 2010, Valletta, Malta.
European Language Resources Association.
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References II
Cuadros, M., Padr´o, L., and Rigau, G. (2012).
Highlighting relevant concepts from topic signatures.
In Calzolari, N., Choukri, K., Declerck, T., Dogan, M. U., Maegaard, B., Mariani, J.,
Odijk, J., and Piperidis, S., editors, Proceedings of the Eighth International
Conference on Language Resources and Evaluation (LREC-2012), Istanbul, Turkey,
May 23-25, 2012, pages 3841–3848. European Language Resources Association
(ELRA).
Das, D., Chen, D., Martins, A. F. T., Schneider, N., and Smith, N. A. (2014).
Frame-semantic parsing.
Computational Linguistics, 40(1):9–56.
de Lacalle, M. L., Laparra, E., and Rigau, G. (2014).
Predicate Matrix: extending SemLink through WordNet mappings.
In Calzolari, N., Choukri, K., Declerck, T., Loftsson, H., Maegaard, B., Mariani, J.,
Moreno, A., Odijk, J., and Piperidis, S., editors, Proceedings of the Ninth
International Conference on Language Resources and Evaluation (LREC-2014),
Reykjavik, Iceland, May 26-31, 2014., pages 903–909. European Language
Resources Association (ELRA).
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References III
Gangemi, A. and Mika, P. (2003).
Understanding the semantic web through descriptions and situations.
In [Meersman et al., 2003], pages 689–706.
Gangemi, A., Presutti, V., Recupero, D. R., Nuzzolese, A. G., Draicchio, F., and
Mongiovi, M. (2016).
Semantic Web Machine Reading with FRED.
Semantic Web.
Meersman, R., Tari, Z., and Schmidt, D. C., editors (2003).
On The Move to Meaningful Internet Systems 2003: CoopIS, DOA, and ODBASE -
OTM Confederated International Conferences, CoopIS, DOA, and ODBASE 2003,
Catania, Sicily, Italy, November 3-7, 2003, volume 2888 of Lecture Notes in
Computer Science. Springer.
Moro, A., Raganato, A., and Navigli, R. (2014).
Entity Linking meets Word Sense Disambiguation: a Uniﬁed Approach.
Transactions of the Association for Computational Linguistics (TACL), 2:231–244.
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References IV
Nuzzolese, A. G., Gangemi, A., Presutti, V., Ciancarini, P., and Musetti, A. (2012).
Automatic Typing of DBpedia Entities.
In Proc. of the International Semantic Web Conference (ISWC), Boston, MA, US.
Rouces, J., de Melo, G., and Hose, K. (2015).
Framebase: Representing n-ary relations using semantic frames.
In Gandon, F., Sabou, M., Sack, H., d’Amato, C., Cudr´e-Mauroux, P., and
Zimmermann, A., editors, The Semantic Web. Latest Advances and New Domains -
12th European Semantic Web Conference, ESWC 2015, Portoroz, Slovenia, May 31
- June 4, 2015. Proceedings, volume 9088 of Lecture Notes in Computer Science,
pages 505–521. Springer.
Staiano, J. and Guerini, M. (2014).
Depeche Mood: a Lexicon for Emotion Analysis from Crowd Annotated News.
In Proceedings of the 52nd Annual Meeting of the Association for Computational
Linguistics, ACL 2014, June 22-27, 2014, Baltimore, MD, USA, Volume 2: Short
Papers, pages 427–433. The Association for Computer Linguistics.
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Framester: A Wide Coverage Linguistic Linked Data Hub

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