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Institute of Applied Data Science


Professor Massimo Poesio

Massimo Poesio

Professor of Computational Linguistics & Turing Fellow

School of Electronic Engineering and Computer Science
Peter Landin, CS 404
+44 20 7882 5773


Natural Language Processing, machine translation, visually grounded and textual semantic models


His research interests are in the semantics of natural language and in computational methods for semantic analysis, particularly in the areas of anaphora resolution and in dialogue. One of the main areas of research at the moment is the use of games to collect data to support computational linguistics (‘Games with a purpose’). His work on the organisation and acquisition of conceptual knowledge has involved using machine learning techniques to acquire evidence about common sense from corpora and brain data. 


Publications of specific relevance to Applied Data Science


Fornaciari T, Cagnina L, Rosso P and Poesio M (2020). Fake opinion detection: how similar are crowdsourced datasets to real data? Language Resources and Evaluation  vol. 54, (4) 1019-1058. 10.1007/s10579-020-09486-5
Poesio M (2020). Ambiguity. The Wiley Blackwell Companion to Semantics  10.1002/9781118788516.sem098
Alhelbawy A, Lattimer M, Kruschwitz U, Fox C and Poesio M (2020). An NLP-Powered Human Rights Monitoring Platform. Expert Systems With Applications  vol. 153, 10.1016/j.eswa.2020.113365
Alhelbawy A, Lattimer M, Kruschwitz U, Fox C and Poesio M (2020). An NLP-Powered Human Rights Monitoring Platform. Elsevier  Expert Systems With Applications  100023-100023. 10.1016/j.eswa.2020.113365


Uryupina O, Artstein R, Bristot A, Cavicchio F, Delogu F, Rodriguez KJ and Poesio M (2019). Annotating a broad range of anaphoric phenomena, in a variety of genres: The ARRAU Corpus. Natural Language Engineering  10.1017/S1351324919000056


Paun S, Carpenter B, Chamberlain J, Hovy D, Kruschwitz U and Poesio M (2018). Comparing Bayesian Models of Annotation. Transactions of The Association For Computational Linguistics  vol. 6, 571-585. 10.1162/tacl_a_00040
Chamberlain J, Kruschwitz U and Poesio M (2018). Optimising crowdsourcing efficiency: Amplifying human computation with validation. Walter De Gruyter Gmbh  It - Information Technology  vol. 60, (1) 41-49. 10.1515/itit-2017-0020


Poesio M, Chamberlain J and Kruschwitz U (2017). Phrase Detectives. Handbook of Linguistic Annotation  10.1007/978-94-024-0881-2_43
Poesio M, Chamberlain J and Kruschwitz U (2017). Crowdsourcing. Handbook of Linguistic Annotation  10.1007/978-94-024-0881-2_10
POESIO M, ANDERSON A, Clark S and Kiela D (2017). Visually grounded and textual semantic models differentially decode brain activity associated with concrete and abstract nouns. Association For Computational Linguistics  Transactions of The Association For Computational Linguistics  vol. 5, 17-30. 10.1162/tacl_a_00043


Ginzburg J and Poesio M (2016). Grammar Is a System That Characterizes Talk in Interaction. Frontiers Media  Front Psychol  vol. 7, 1938-1938. 10.3389/fpsyg.2016.01938
Rieser H and Poesio M (2016). Pandora's Box Opened. Theoretical Linguistics  vol. 42, (3-4) 305-318. 10.1515/tl-2016-0015
Steinberger J, Kabadjov M and Poesio M (2016). Coreference Applications to Summarization. Anaphora Resolution  10.1007/978-3-662-47909-4_15
Poesio M (2016). Linguistic and Cognitive Evidence About Anaphora. Anaphora Resolution  10.1007/978-3-662-47909-4_2
Poesio M, Stuckardt R, Versley Y and Vieira R (2016). Early Approaches to Anaphora Resolution: Theoretically Inspired and Heuristic-Based. Anaphora Resolution  10.1007/978-3-662-47909-4_3
Poesio M, Pradhan S, Recasens M, Rodriguez K and Versley Y (2016). Annotated Corpora and Annotation Tools. Anaphora Resolution  10.1007/978-3-662-47909-4_4
Uryupina O, Kabadjov M and Poesio M (2016). Detecting Non-reference and Non-anaphoricity. Anaphora Resolution  10.1007/978-3-662-47909-4_13
Poesio M, Stuckardt R and Versley Y (2016). Challenges and Directions of Further Research. Anaphora Resolution  10.1007/978-3-662-47909-4_17
Versley Y, Poesio M and Ponzetto S (2016). Using Lexical and Encyclopedic Knowledge. Anaphora Resolution  10.1007/978-3-662-47909-4_14
Poesio M (2016). Discourse. The Oxford Handbook of Computational Linguistics 2nd Edition  10.1093/oxfordhb/9780199573691.013.32


Anderson AJ, Bruni E, Lopopolo A, Poesio M and Baroni M (2015). Reading visually embodied meaning from the brain: Visually grounded computational models decode visual-object mental imagery induced by written text. Neuroimage  vol. 120, 309-322. 10.1016/j.neuroimage.2015.06.093
Sikdar UK, Ekbal A, Saha S, Uryupina O and Poesio M (2015). Differential evolution-based feature selection technique for anaphora resolution. Soft Computing  vol. 19, (8) 2149-2161. 10.1007/s00500-014-1397-3
Althobaiti M, Kruschwitz U and Poesio M (2015). Combining Minimally-supervised Methods for Arabic Named Entity Recognition. Transactions of The Association For Computational Linguistics  vol. 3, 243-255. 10.1162/tacl_a_00136
Poesio M (2015). Weak Definites. Semantics and Linguistic Theory  10.3765/salt.v0i0.2465


Akama H, Murphy B, Lei MM and Poesio M (2014). Cross-participant modelling based on joint or disjoint feature selection: an fMRI conceptual decoding study. Applied Informatics  vol. 1, (1) 10.1186/2196-0089-1-1
Gu Y, Poesio M and Murphy B (2014). EEG study of the cortical representation and classification of the emotional connotations in words. Bmc Neuroscience  vol. 15, (Suppl 1) 10.1186/1471-2202-15-s1-p81
Anderson AJ, Murphy B and Poesio M (2014). Discriminating taxonomic categories and domains in mental simulations of concepts of varying concreteness. Journal of Cognitive Neuroscience  vol. 26, (3) 658-681. 10.1162/jocn_a_00508
Cavicchio F, Melcher D and Poesio M (2014). The effect of linguistic and visual salience in visual world studies. Frontiers in Psychology  vol. 5, (MAR) 10.3389/fpsyg.2014.00176


Fornaciari T and Poesio M (2013). Automatic deception detection in Italian court cases. Artificial Intelligence and Law  vol. 21, (3) 303-340. 10.1007/s10506-013-9140-4
Sikdar UK, Ekbal A, Saha S, Uryupina O and Poesio M (2013). Anaphora resolution for bengali: An experiment with domain adaptation. Computacion Y Sistemas  vol. 17, (2) 137-146.
Gu Y, Cazzolli G, Murphy B, Miceli G and Poesio M (2013). EEG study of the neural representation and classification of semantic categories of animals vs tools in young and elderly participants. Bmc Neuroscience  vol. 14, (Suppl 1) 10.1186/1471-2202-14-s1-p318
Chamberlain J, Fort K, Kruschwitz U, Lafourcade M and Poesio M (2013). Using Games to Create Language Resources: Successes and Limitations of the Approach. The People’S Web Meets Nlp  10.1007/978-3-642-35085-6_1
Poesio M, Chamberlain J, Kruschwitz U, Robaldo L and Ducceschi L (2013). Phrase detectives: Utilizing collective intelligence for internet-scale language resource creation. Acm Transactions On Interactive Intelligent Systems  vol. 3, (1) 10.1145/2448116.2448119
Chamberlain J, Kruschwitz U and Poesio M (2013). Methods for engaging and evaluating users of human computation systems. Handbook of Human Computation  10.1007/978-1-4614-8806-4_54


Akama H, Murphy B, Na L, Shimizu Y and Poesio M (2012). Decoding semantics across fMRI sessions with different stimulus modalities: A practical MVPA study. Frontiers in Neuroinformatics  vol. 6, (JULY 2012) 10.3389/fninf.2012.00024
Cavicchio F and Poesio M (2012). (Non)cooperative dialogues: The role of emotions. Human Factors  vol. 54, (4) 546-559. 10.1177/0018720812440279
Cavicchio F and Poesio M (2012). The Rovereto Emotion and Cooperation Corpus: A new resource to investigate cooperation and emotions. Language Resources and Evaluation  vol. 46, (1) 117-130. 10.1007/s10579-011-9163-y


Poesio M, Diewald N, Stührenberg M, Chamberlain J, Jettka D, Goecke D and Kruschwitz U (2011). Markup infrastructure for the anaphoric bank: Supporting web collaboration. Studies in Computational Intelligence  vol. 370, 175-195. 10.1007/978-3-642-22613-7_10
Poesio M and Rieser H (2011). An Incremental Model of Anaphora and Reference Resolution Based on Resource Situations. Dialogue & Discourse  vol. 2, (1) 235-277. 10.5087/dad.2011.110
Murphy B, Poesio M, Bovolo F, Bruzzone L, Dalponte M and Lakany H (2011). EEG decoding of semantic category reveals distributed representations for single concepts. Brain and Language  vol. 117, (1) 12-22. 10.1016/j.bandl.2010.09.013


Baroni M, Murphy B, Barbu E and Poesio M (2010). Strudel: A corpus-based semantic model based on properties and types. Cognitive Science  vol. 34, (2) 222-254. 10.1111/j.1551-6709.2009.01068.x
Poesio M and Rieses H (2010). Completions, Coordination, and Alignment in Dialogue. Dialogue & Discourse  vol. 1, (1) 10.5087/dad.2010.001
Kabadjov M, Steinberger J, Steinberger R, Poesio M and Pouliquen B (2010). Enhancing N-Gram-Based Summary Evaluation Using Information Content and a Taxonomy. Advances in Information Retrieval  10.1007/978-3-642-12275-0_71


Poesio M, Day D and Mani I (2009). Janet Hitzeman Obituary. Computational Linguistics  vol. 35, (4) 476-479.
Poesio M, Day D and Mani I (2009). Janet Hitzeman. Computational Linguistics  vol. 35, (4) 475-481. 10.1162/coli.2009.35.4.35411
Karamanis N, Poesio M, Mellish C and Oberlander J (2009). Evaluating centering for information ordering using corpora. Computational Linguistics  vol. 35, (1) 29-46. 10.1162/coli.07-036-R2-06-22


Poesio M and Artstein R (2008). Introduction to the special issue on ambiguity and semantic judgments. Research On Language and Computation  vol. 6, (3-4) 241-245. 10.1007/s11168-008-9057-3
Poesio M (2008). Linguistic Claims Formulated in Terms of Centering Linguistic Claims Formulated in Terms of Centering A Re-Examination Using Parametric CB-Tracking Techniques. Reference: Interdisciplinary Perspectives  10.1093/acprof:oso/9780195331639.003.0009
Artstein R and Poesio M (2008). Inter-coder agreement for computational linguistics. Computational Linguistics  vol. 34, (4) 555-596. 10.1162/coli.07-034-R2
Poesio M and Almuhareb A (2008). Extracting concept descriptions from the web: The importance of attributes and values. Frontiers in Artificial Intelligence and Applications  vol. 167, (1) 29-44.
Poesio M, Reyle U and Stevenson R (2008). Justified Sloppiness In Anaphoric Reference. Computing Meaning  10.1007/978-1-4020-5958-2_2


Steinberger J, Poesio M, Kabadjov MA and Ježek K (2007). Two uses of anaphora resolution in summarization. Information Processing and Management  vol. 43, (6) 1663-1680. 10.1016/j.ipm.2007.01.010
Sanchez-Graillet O and Poesio M (2007). Negation of protein-protein interactions: Analysis and extraction. Bioinformatics  vol. 23, (13) 10.1093/bioinformatics/btm184


Poesio M, Sturt P, Artstein R and Filik R (2006). Underspecification and anaphora: Theoretical issues and preliminary evidence. Discourse Processes  vol. 42, (2) 157-175. 10.1207/s15326950dp4202_4


Poesio M (2005). Domain modelling and NLP: Formal ontologies? Lexica? Or a bit of both? Applied Ontology  vol. 1, 27-33.
Poesio M and Modjeska NN (2005). Focu, Activation, and This-Noun Phrases. Anaphora Processing  10.1075/cilt.263.24poe


Poesio M, Di Eugenio B, Stevenson R and Hitzeman J (2004). Centering: A parametric theory and its instantiations. Computational Linguistics  vol. 30, (3) 309-364. 10.1162/0891201041850911


Garrod S and Poesio M (2002). Plumbing semantic depths in Amsterdam. Trends in Cognitive Sciences  vol. 6, (4) 150-151. 10.1016/S1364-6613(02)01878-8


Vieira R and Poesio M (2000). An Empirically Based System for Processing Definite Descriptions. Computational Linguistics  vol. 26, (4) 539-593. 10.1162/089120100750105948
Vieira R and Poesio M (2000). An empirically based system for processing definite descriptions. Computational Linguistics  vol. 26, (4) 538-593. 10.1162/089120100750105948
Vieira R and Poesio M (2000). Processing definite descriptions in corpora. Corpus-Based and Computational Approaches to Discourse Anaphora  10.1075/scl.3.10vie


Poesio M and Vieira R (1998). A Corpus-based Investigation of Definite Description Use. Computational Linguistics  vol. 24, (2)


Poesio M and Traum DR (1997). Conversational actions and discourse situations. Computational Intelligence  vol. 13, (3) 309-347. 10.1111/0824-7935.00042


Traum DR, Schubert LK, Martin NG, Hwang CH, Heeman P, Ferguson G, Allen JF, Poesio M and Light M (1996). Knowledge representation in the TRAINS-93 conversation system. International Journal of Expert Systems  vol. 9, (1) 173-223.
Poesio M (1996). Logic and lexicon - Pinkal,M. Computational Linguistics  vol. 22, (1) 140-144.


Allen JF, Schubert LK, Ferguson G, Heeman P, Hwang CH, Kato T, Light M, Martin N, Miller B, Poesio M and Traum DR (1995). The TRAINS project: A case study in building a conversational planning agent. Journal of Experimental and Theoretical Artificial Intelligence  vol. 7, (1) 7-48. 10.1080/09528139508953799


Poesio M (1994). Weak Definites. Semantics and Linguistic Theory  vol. 4, 10.3765/salt.v4i0.2465


Poesio M (1991). Scope Ambiguity and Inference. 10.21236/ada247448


Horacek H, Bergmann H, Block R, Fliegner M, Gerlach M, Poesio M and Sprenger M (1988). From Meaning to Meaning. KüNstliche Intelligenz  10.1007/978-3-642-74064-0_13


Poesio M and Rullent C (1987). MODIFIED CASEFRAME PARSING FOR SPEECH UNDERSTANDING SYSTEMS. Cselt Technical Reports  vol. 15, (6) 441-446.
Poesio M (1987). An Organization of Lexical Knowledge for Generation. Gwai-87 11th German Workshop On Artifical Intelligence  10.1007/978-3-642-73005-4_10


Grants of specific relevance to Applied Data Science
Human Rights and Information Technology in the Era of Big Data
Mcgregor L, Bhalotra SR, Woods LM, Poesio M, Landman T, Sunkin M, Mcdonald-Maier KD and Fussey P
£4,743,734 Economic and Social Research Council (30-09-2015 - 29-09-2021)
Disagreements and Language Interpretation
Poesio M
EUR2,499,471 European Research Council (01-09-2016 - 31-08-2021)