Abacha, A. B., Shivade, Ch., & Demner-Fushman, D. (2019). Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question Answering. In Proceedings of the 18th BioNLP Workshop and Shared Task (pp. 370—379). Florence, Association for Computational Linguistics.
Google Scholar

Adams, B. W. (1975). The Logic of Conditionals. Dordrecht, Reidel.
Google Scholar

Agirre, E., Diab, M., Cer, D., & Gonzalez-Agirre, A. (2012). SemEval-2012 task 6: A pilot on semantic textual similarity. In The First Joint Conference on Lexical and Computational Semantics — Volume 1: Proceedings of the Main Conference and the Shared Task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (pp. 385—393). Montréal, Association for Computational Linguistics.
Google Scholar

Aijmer, K. (1996). Conversational Routines in English: Convention and Creativity. London, Longman.
Google Scholar

Anand, P., & Hacquard, V. (2014). Factivity, belief and discourse. In L. Crnic & U. Sauerland (Eds.), The Art and Craft of Semantics: A Festschrift for Irene Heim (pp. 69—90). MITWPL.
Google Scholar

Androutsopoulos, I., & Malakasiotis, P. (2010). A survey of paraphrasing and textual entailment methods. Journal of Artificial Intelligence Research, 38, 135—187.
Google Scholar

Arora, R., Singh, P., Goyal, H., Singhal, S., & Vijayvargiya, S. (2021). Comparative Question Answering System based on Natural Language Processing and Machine Learning. In 2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS) (pp. 373—378). IEEE.
Google Scholar

Baglini, R., & Francez, I. (2016). The Implications of managing. Journal of Semantics, 33(3), 541—560.
Google Scholar

Baldwin, T., & Kim, S. N. (2010). Multiword expressions. In N. Indurkhya & F. J. Damerau
Google Scholar

(Eds.), Handbook of Natural Language Processing (2nd ed., pp. 267—292). CRC Press, Taylor and Francis Group, Boca Raton, FL.
Google Scholar

Banyś, W. (1987a). « Iffyness » des verbes transitifs causatifs et structure thème-rhème. Neophilologica, 7.
Google Scholar

Banyś, W. (1987b). Implications actualisationnelles des « si-verbes » à la Karttunen. Linguistica Silesiana, 8.
Google Scholar

Banyś, W. (1989). Théorie sémantique et « si…alors ». Aspects sémantico-logiques de la proposition conditionnelle. Katowice, Wydawnictwo Uniwersytetu Śląskiego.
Google Scholar

Banyś, W. (1990). Généricité et implication ou l’histoire, souvent déformée d’un couple. Equivalences.
Google Scholar

Banyś, W. (2021). Perspectives pour la linguistique : de la linguistique descriptive à la linguistique explicative. Neophilologica, 33, 1—29.
Google Scholar

Barzilay, R., & McKeown, K. (2005). Sentence Fusion for Multidocument News Summarization. Computational Linguistics, 31(3), 297—328.
Google Scholar

Bernardy, J.-Ph., & Chatzikyriakidis, S. (2020). Improving the precision of natural textual entailment problem datasets. In LREC 2020: 12th International Conference on Language Resources and Evaluation, Conference Proceedings (pp. 6835—6840). Marseille, European Language Resources Association.
Google Scholar

Bhagat, R., & Hovy, D. (2013). What Is a Paraphrase? Computational Linguistics, 39(3), 463—472.
Google Scholar

Biber, D., Conrad, S., & Cortes, V. (2003). Lexical bundles in speech and writing: An initial taxonomy. In A. Wilson, P. Rayson & T. McEnery (Eds.), Corpus linguistics by the Lune: A festschrift for Geoffrey Leech (pp. 71—92). Frankfurt, Peter Lang.
Google Scholar

Bittar, A., Amsili, P., Denis, P., & Danlos, L. (2011). French TimeBank: An ISO-TimeML
Google Scholar

annotated reference corpus. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers (Vol. 2, pp. 130—134). Portland, Oregon, Association for Computational Linguistics.
Google Scholar

Boër, S. E., & Lycan, W. G. (1973). Invited Inferences and Other Unwelcome Guests. Papers in Linguistics, 6(1-4), 483—505.
Google Scholar

Bogusławski, A. (1986). The Problem of Ifs vs. Logical Implication Revisited. In Proceedings of the Third International Congress of the IASS Palermo, 1984 (Vol. 1, pp. 81—88). Berlin — New York, Mouton de Gruyter, Association for Computational Linguistics.
Google Scholar

Boons, J.-P., Guillet, A., & Leclère, Chr. (1976). La structure des phrases simples en français : constructions intransitives. Genève, Droz.
Google Scholar

Bouveret, M., & Fillmore, Ch. (2008). Matching Verbo-nominal Constructions in FrameNet with Lexical Functions in MTT. In Proceedings of the 13th EURALEX International Congress (pp. 297—308). Barcelona, Institut Universitari de Lingüística Aplicada, Universitat Pompeu Fabra.
Google Scholar

Boyer, M., & Lapalme, G. (1985). Generating paraphrases from meaning‐text semantic networks. Computational Intelligence, 1, 103—117.
Google Scholar

Breitholtz, E. (2021). Enthymemes and Topoi in Dialogue. The Use of Common Sense Reasoning in Conversation. Leiden — Boston, Brill.
Google Scholar

Callison-Burch, C., Koehn, Ph., & Osborne, M. (2006). Improved Statistical Machine Translation Using Paraphrases. In Proceedings of the Human Language Technology Conference of the North American Chapter of the ACL (pp. 17—24). New York, Association for Computational Linguistics.
Google Scholar

Ceniza, C. R. (1988). Material implication and entailment. Notre Dame Journal of Formal Logic, 29(4), 510—519.
Google Scholar

Cer, D., Diab, M., Agirre, E., Lopez-Gazpio, I., & Specia, L. (2017). SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation. In Proceedings of the 11th International Workshop on Semantic Evaluation (pp. 1—14). Vancouver, Association for Computational Linguistics.
Google Scholar

Chomsky, N. (1965). Aspects of the Theory of Syntax. Cambridge (Massachusetts), MIT Press.
Google Scholar

Clarke, J., & Lapata, M. (2008). Global Inference for Sentence Compression: An Integer Linear Programming Approach. Journal of Artificial Intelligence Research, 31, 399—429.
Google Scholar

Constant, M., & Tolone, E. (2010). A generic tool to generate a lexicon for NLP from Lexicon-
Google Scholar

Grammar tables. In Proceedings of the 27th international congress on lexicon and grammar. Volume 1 of Lingue d’Europa e del Mediterraneo, Grammatica comparata (pp. 79—93). Aracne, Association for Computational Linguistics.
Google Scholar

Crouch, R., Sauri, R., & Fowler, A. (2005). AQUAINT pilot knowledge-based evaluation: Annotation guidelines. https://parc-public.pages-external.parc.com/xle/isl/groups/nltt/papers/aquaint_kb_pilot_evaluation_guide.pdf
Google Scholar

Czerepowicka, M., & Savary, A. (2018). SEJF — A Grammatical Lexicon of Polish Multiword Expressions. In Z. Vetulani, J. Mariani & M. Kubis (Eds.), Human Language Technology. Challenges for Computer Science and Linguistics (LTC 2015. Lecture Notes in Computer Science: Vol. 10930) (pp. 59—73). Springer, Cham.
Google Scholar

Dagan, I., Roth, D., Sammons, M., & Zanzotto, F. M. (2013). Recognizing Textual Entailment: Models and Applications. Williston, VT, Morgan & Claypool.
Google Scholar

Danlos, L. (Dir.). (1988). Langages, 90 : Les expressions figées. Paris, Larousse.
Google Scholar

Deppermann, A. (2018). Inferential Practices in Social Interaction: A Conversation-Analytic Account. Open Linguistics, 4, 35—55.
Google Scholar

Devlin, J., Chang, M., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. ArXiv, abs /1810.04805, 4171—4186.
Google Scholar

Drapeau, L., & Gérard, J. (1973). Là où les implications se compliquent. Cahier de linguistique, 3, 73—104. https://doi.org/10.7202/800023ar
Google Scholar

Duboue, P., & Chu-Carroll, J. (2006). Answering the question you wish they had asked: The impact of paraphrasing for Question Answering. In Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers (pp. 33—36). New York, Association for Computational Linguistics.
Google Scholar

Ducrot, O. (1972). Dire et ne pas dire. Principes de sémantique linguistique. Paris, Herman.
Google Scholar

Ducrot, O. (1977). Postface : Note sur la présupposition et le sens littéral. In P. Henry, Le mauvais outil : langue, sujet et discours (p. 169—203). Paris, Klincksieck.
Google Scholar

Egan, Th. (2008). Non-finite complementation: A usage-based study of infinitive and -ing clauses in English. Rodopi, Amsterdam.
Google Scholar

Ehmer, O., & Rosemeyer, M. (2018). Inferences in Interaction and Language Change. Open Linguistics, 4, 536—551.
Google Scholar

Elshazly, M., Haggag, M., & Ehssan, S. A. (2021). Natural Language Processing Applications: A New Taxonomy using Textual Entailment. International Journal of Advanced Computer Science and Applications, 12(5), 676—690.
Google Scholar

Erman, B., & Warren, B. (2000). The idiom principle and the open choice principle. Text & Talk, 20, 29—62.
Google Scholar

Falk, I., & Martin, F. (2017a). Towards an Inferential Lexicon of Event Selecting Predicates for French. In IWCS 2017 — 12th International Conference on Computational Semantics — Long papers. ArXiv abs / 1710.01095 (HAL Id: Hal-01597887).
Google Scholar

Falk, I., & Martin, F. (2017b). Towards a Lexicon of Event-Selecting Predicates for a French FactBank. In Proceedings of the Workshop Computational Semantics Beyond Events and Roles (pp. 16—21). Valencia, Association for Computational Linguistics.
Google Scholar

Fasciolo, M. (2017). Les verbes d’occurrence sont-ils des supports des noms ? Études de linguistique appliquée, 186(2), 197—210.
Google Scholar

Finch, A. M., Watanabe, T., Akiba, Y., & Sumita, E. (2004). Paraphrasing as Machine Translation. Journal of Natural Language Processing, 11(5), 87—110.
Google Scholar

Foster, P. (2001). Rules and routines: A consideration of their role in the task-based language production of native and non-native speakers. In M. Bygate, P. Skehan & M. Swain (Eds.), Researching pedagogic tasks: Second language learning, teaching, and testing (pp. 75—93). Harlow, Longman.
Google Scholar

Fuchs, C. (1994). Paraphrase et énonciation. Paris, Ophrys.
Google Scholar

Galanis, D., & Androutsopoulos, I. (2010). An extractive supervised two-stage method for sentence compression. In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics (pp. 885—893). Los Angeles, Association for Computational Linguistics.
Google Scholar

Gantt, W., Kane, B., & White, A. S. (2020). Natural Language Inference with Mixed Effects. In Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics (pp. 81—87). Barcelona, Association for Computational Linguistics.
Google Scholar

Geiger, A., Cases, I., Karttunen, L., & Potts, Ch. (2019). Posing Fair Generalization Tasks for Natural Language Inference. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) (pp. 4485—4495). Hong Kong, Association for Computational Linguistics.
Google Scholar

Geis, M., & Zwicky, A. (1971). On invited inferences. Linguistic Inquiry, 2, 561—565.
Google Scholar

Giry-Schneider, J. (1987). Les prédicats nominaux en français : les phrases simples à verbe support. Genève, Droz.
Google Scholar

Givón, T. (1972). Forward Implications, Backward Presuppositions, and the Time Axis of Verbs. In J.-P. Kimball (Ed.), Syntax and Semantics (Vol. 1, pp. 29—50). New York, Academic Press.
Google Scholar

Gréciano, G. (Éd.). (2000). Micro- et macrolexèmes et leur figement discursif. Louvain — Paris, Peeters.
Google Scholar

Grefenstette, G., & Teufel, S. (1995). Corpus-based method for automatic identification of support verbs for nominalizations. In Proceedings of the Seventh Conference on European Chapter of the Association for Computational Linguistics (pp. 98—103). Dublin, Association for Computational Linguistics.
Google Scholar

Grimshaw, J. (2015). The light verbs Say and Say. In I. Toivonen, P. Csuri & E. van der Zee (Eds.), Structures in the Mind: Essays on Language, Music, and Cognition (pp. 79—99). Cambridge (Massachusetts) — London (England), MIT Press.
Google Scholar

Gross, G. (1988). Degré de figement des noms composés. Langages, 90, 57—72.
Google Scholar

Gross, G. (1993). Trois applications de la notion de verbe support. L’Information grammaticale, 59, 16—22.
Google Scholar

Gross, G. (1994). Classes d’objets et description de verbes. Langages, 115, 15—30.
Google Scholar

Gross, G. (1996). Les expressions figées en français. Noms composés et autres locutions. Paris, Ophrys.
Google Scholar

Gross, G. (2012). Manuel d’analyse linguistique. Approche sémantico-syntaxique du lexique. Villeneuve-d’Ascq, Presses universitaires du Septentrion.
Google Scholar

Gross, G. (2017). Petit historique de la notion de verbes supports. Cahiers de lexicologie, 111, 121—144.
Google Scholar

Gross, G. (2022). Pour un recensement systématique des verbes supports. Neophilologica, 34, 1—21.
Google Scholar

Gross, M. (1975). Méthodes en Syntaxe. Paris, Hermann.
Google Scholar

Gross, M. (1988a). Les limites de la phrase figée. Langages, 90, 7—22.
Google Scholar

Gross, M. (1988b). Sur les phrases figées complexes du français. Langue française, 77, 47—70.
Google Scholar

Gross, M. (1998). La fonction sémantique des verbes supports. Travaux de Linguistique, 37, 25—46.
Google Scholar

Grossmann, Fr., & Krzyżanowska, A. (2020). Analyser les formules pragmatiques de la conversation : problèmes de méthodes dans une perspective lexicographique. Neophilologica, 32, 59—76.
Google Scholar

Grossmann, Fr., Mejri, S., & Sfar, I. (Dir.). (2017). La phraséologie : sémantique, syntaxe, discours. Paris, Honoré Champion.
Google Scholar

Grossmann, Fr., & Tutin, A. (2003). Les Collocations : analyse et traitement. Amsterdam, Éditions de Werelt.
Google Scholar

Guillet, A., & Leclère, Chr. (1992). La structure des phrases simples en français. Les constructions transitives locatives. Genève, Droz.
Google Scholar

Gupta, A., Kaur, M., Mirkin, S., Singh, A., & Goyal, A. (2014). Text Summarization through Entailment-based Minimum Vertex Cover. In Proceedings of the Third Joint Conference on Lexical and Computational Semantics (pp. 75—80). Dublin, Association for Computational Linguistics.
Google Scholar

Gupta, A., Kaur, M., & Mittal, S. (2021). PE-MSC: partial entailment-based minimum set cover for text summarization. Knowledge and Information Systems, 63, 1045—1068.
Google Scholar

Halliday, M. A. K. (1994). An Introduction to Functional Grammar. London, Edward Arnold.
Google Scholar

Harabagiu, S., & Hickl, A. (2006). Methods for Using Textual Entailment in Open-Domain Question Answering. In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (pp. 905—912). Sydney, Association for Computational Linguistics.
Google Scholar

Harabagiu, S., Maiorano, S. J., & Pasca, M. A. (2003). Open-domain textual question answering techniques. Natural Language Engineering, 9(3), 231—267.
Google Scholar

Harris, Z. (1951). Methods in Structural Linguistics. Chicago, University of Chicago Press.
Google Scholar

Huang, Y. (2011). Types of inference: entailment, presupposition, and implicature.
Google Scholar

In W. Bublitz & N. R. Norrick (Eds.), Foundations of Pragmatics (pp. 397—421). Berlin — New York, De Gruyter.
Google Scholar

Iordanskaja, L., Kittredge, R., & Polguère, A. (1991). Lexical Selection and Paraphrase in a Meaning-Text Generation Model. In C. L. Paris, W. R. Swartout & W. C. Mann (Eds.), Natural Language Generation in Artificial Intelligence and Computational Linguistics (The Kluwer International Series in Engineering and Computer Science: Vol. 119) (pp. 293—312). Boston, Springer.
Google Scholar

Kane, B., Gantt, W., & White, A. S. (2022). Intensional Gaps: Relating veridicality, doxasticity, bouleticity, and neg-raising. Semantics and Linguistic Theory, 31, 570—605.
Google Scholar

Karolak, S. (1984). Składnia wyrażeń predykatywnych [Syntaxe des expressions prédicatives]. In Z. Topolińska (Ed.), Gramatyka współczesnego języka polskiego. Składnia [Grammaire du polonais contemporain. Syntaxe] (s. 11—211). Warszawa, Wydawnictwo Naukowe PWN.
Google Scholar

Karttunen, L. (1971a). Implicative Verbs. Language, 47(2), 340—358.
Google Scholar

Karttunen, L. (1971b [1973a]). The Logic of English Predicate Complement Constructions. In W. P. Lehmann & R. Stachowitz (Eds.), Feasibility Study on Fully Automatic High Quality Translation (pp. 119—155). Austin, University of Texas Indiana. [Traduction française : (1973). La logique des constructions anglaises à complément prédicatif. Langages, 30, 56—80].
Google Scholar

Karttunen, L. (1974). Presupposition and linguistic context. Theoretical Linguistics, 1, 181—193.
Google Scholar

Karttunen, L. (1973b). Presuppositions of Compound Sentences. Linguistic Inquiry, 4(2), 169—193.
Google Scholar

Karttunen, L. (2012). Simple and Phrasal Implicatives. In *SEM 2012: The First Joint Conference on Lexical and Computational Semantics — Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (pp. 124—131). Montréal, Association for Computational Linguistics.
Google Scholar

Karttunen, L. (2013). You Will Be Lucky To Break Even. In T. H. King & V. de Paiva (Eds.), From Quirky Case to Representing Space: Papers in Honor of Annie Zaenen (pp. 167—180). Stanford, CSLI Publications,
Google Scholar

Karttunen, L., & Cases, I. (2019, May 29). Teaching a Neural Network to Reason with Implicatives [Conference presentation]. CLASP, University of Gothenburg.
Google Scholar

Karttunen, L., Cases, I., & Supaniratisai, G. (2016, December 5). A Learning Corpus for Implicatives [Presentation at the Semantics and Pragmatics Group meeting]. CSLI, Stanford.
Google Scholar

Karttunen, L., & Peters, S. (1979). Conventional Implicature. Syntax and Semantics, 11, 1—56.
Google Scholar

Kauchak, D., & Barzilay, R. (2006). Paraphrasing for Automatic Evaluation. In Proceedings of the Human Language Technology Conference of the NAACL. Main Conference (pp. 455—462). New York, Association for Computational Linguistics.
Google Scholar

Kaur, M., & Srivastava, D. (2019). Text Summarization using Partial Textual Entailment based Graphs. In International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon) (pp. 366—374). Faridabad, IEEE.
Google Scholar

Keenan, E. L. (1971). Two Kinds of Presupposition in Natural Language. In Ch. Fillmore & J. Langendoen (Eds.), Studies in Linguistic Semantics (pp. 45—54). New York. Holt, Rinehart & Winston.
Google Scholar

Kiparsky, P., & Kiparsky, C. (1971). Fact. In D. Steinberg & L. A. Jakobovits (Eds.), Semantics: An interdisciplinary reader (pp. 345—369). Cambridge, Cambridge University Press.
Google Scholar

Kleiber, G. (2004). Item lexical, mots construits et polylexicalité vus sous l’angle de la dénomination. Syntaxe et Sémantique, 5, 31—46.
Google Scholar

Klein, J. R., & Lamiroy, B. (2016). Le figement : Unité et diversité. Collocations, expressions figées, phrases situationnelles, proverbes. L’Information grammaticale, 148, 15—20.
Google Scholar

Klemen, M., & Robnik-Šikonja, M. (2021). Extracting and filtering paraphrases by bridging natural language inference and paraphrasing. arXiv preprint arXiv:2111.07119v1. https://arxiv.org/pdf/2111.07119.pdf
Google Scholar

Knight, K., & Marcu, D. (2002). Summarization beyond sentence extraction: A probabilistic approach to sentence compression. Artificial Intelligence, 139, 91—107.
Google Scholar

Koehn, Ph., Birch, A., & Steinberger, R. (2009). 462 Machine Translation Systems for Europe. In MT Summit XII: proceedings of the twelfth Machine Translation Summit (pp. 65—72). Ottawa, Association for Machine Translation in the Americas.
Google Scholar

Kovatchev, V., Gold, D., Martí, A., Salamó, T., & Zesch, T. (2020). Decomposing and comparing meaning relations: Paraphrasing, textual entailment, contradiction, and specificity. In Proceedings of the Twelfth Language Resources and Evaluation Conference (pp. 5782—5791). Marseille, European Language Resources Association.
Google Scholar

Kraif, O., & Tutin, A. (2016). Introduction. Cahiers de lexicologie : Phraséologie et linguistique appliquée, 108, 9—19.
Google Scholar

Lamiroy, B. (Éd.). (1998a). Travaux de Linguistique, 37 : Le lexique-grammaire. Louvain-la-Neuve, Duculot.
Google Scholar

Lamiroy, B. (1998b). Le lexique-grammaire essai de synthèse. Travaux de Linguistique, 37, 7—23.
Google Scholar

Lan, W., & Xu, W. (2018). Neural Network Models for Paraphrase Identification, Semantic Textual Similarity, Natural Language Inference, and Question Answering. In Proceedings of the 27th International Conference on Computational Linguistics (pp. 3890—3902). Santa Fe, Association for Computational Linguistics.
Google Scholar

Lareau, Fr. (2002), La synthèse automatique de paraphrases comme outil de vérification des dictionnaires et grammaires de type Sens-Texte [Mémoire de maîtrise]. Montréal, Université de Montréal.
Google Scholar

Lareau, Fr., Dras, M., Börschinger, B., & Dale, R. (2011). Collocations in Multilingual Natural Language Generation: Lexical Functions meet Lexical Functional Grammar. In Proceedings of Australasian Language Technology Association Workshop (pp. 95—104). Canberra, Association for Computational Linguistics.
Google Scholar

Leclère, Chr. (1990). Organisation du Lexique-grammaire des verbes français. Langue française, 87, 112—122.
Google Scholar

Leclère, Chr. (1998). Travaux récents en lexique-grammaire. Travaux de Linguistique, 37, 155—186.
Google Scholar

Lepage, Y., & Denoual, E. (2005). Automatic generation of paraphrases to be used as translation references in objective evaluation measures of machine translation. In Proceedings of the Third International Workshop on Paraphrasing (IWP2005) (pp. 57—64). Jeju, Association for Computational Linguistics.
Google Scholar

Lin, C., & Hovy, E. H. (2003). Automatic Evaluation of Summaries Using N-gram Co-
Google Scholar

Occurrence Statistics. In Proceedings of HLT-NAACL 2003, Main Papers (pp. 71—78). Edmonton, Association for Computational Linguistics.
Google Scholar

Lin, Ph. (2018). The prosody of formulaic sequences: A corpus and discourse approach. London — New York, Bloomsbury.
Google Scholar

Liu, B., Wei, H., Niu, D., Chen, H., & He, Y. (2020). Asking questions, the human way: Scal-
Google Scholar

able Question-Answer Generation from Text Corpus. arXiv:2002.00748v2
Google Scholar

Mani, I. (2001). Automatic Summarization. Amsterdam, John Benjamins.
Google Scholar

Marneffe, M.-C. de, Manning, C. D., & Potts, C. (2011). Veridicality and utterance meaning. In Proceedings of the Fifth IEEE International Conference on Semantic Computing: Workshop on Semantic Annotation for Computational Linguistic Resources (pp. 430—437). Stanford, IEEE Computer Society Press.
Google Scholar

Marsi, E., Krahmer, E. J., & Bosma, W. (2007). Dependency-based paraphrasing for recog-
Google Scholar

nizing textual entailment. In Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing — RTE (pp. 83—88). East Stroudsburg, Association for Computational Linguistics.
Google Scholar

Martin, R. (1976). Inférence, antonymie et paraphrase. Paris, Klincksieck.
Google Scholar

Mayhew, S., Bicknell, K., Brust, C., McDowell, B., Monroe, W., & Settles, B. (2020). Simultaneous Translation and Paraphrase for Language Education. In Proceedings of the 4th Workshop on Neural Generation and Translation (WNGT 2020) (pp. 232—243). Online, Association for Computational Linguistics.
Google Scholar

McDonald, R. (2007). A study of global inference algorithms in multi-document summarization. In ECIR’07: Proceedings of the 29th European Conference on IR Research (pp. 557—564). Berlin — Heidelberg, Springer-Verlag.
Google Scholar

Mejri, S. (2002). Le figement lexical : nouvelles tendances. Cahiers de lexicologie, 80(1), 213—225.
Google Scholar

Mejri, S. (Dir.). (2003). Cahiers de lexicologie, 82(1) : Figement lexical. Paris, Classiques Garnier.
Google Scholar

Mejri, S. (2004). Introduction : Polysémie et polylexicalité. Syntaxe et sémantique, 5, 13—30.
Google Scholar

Mejri, S., Gross, G., Clas, A., & Baccouche, T. (Éd.). (1998). Le Figement lexical. Actes de la 1re Rencontre linguistique méditerranéenne, Tunis, 17—19 septembre. Tunis, CERES.
Google Scholar

Mel’čuk, I. (1988). Paraphrase et lexique dans la théorie linguistique Sens-Texte. Cahiers de lexicologie, 52(1), 5—50 et 52(2), 5—53.
Google Scholar

Mel’čuk, I. (1992). Paraphrase et Lexique : La Théorie Sens-Texte et le Dictionnaire Explicatif et Combinatoire. In I. Mel’čuk, N. Arbatchewsky-Jumarie, L. Iordanskaja & S. Mantha (Éd.), Dictionnaire Explicatif et Combinatoire du Français Contemporain. Recherches Lexico-Sémantiques III (p. 9—58). Montréal, Presses de l’Université de Montréal.
Google Scholar

Mel’čuk, I. (2004). Verbes supports sans peine. Lingvisticæ Investigationes, 27(2), 203—217.
Google Scholar

Mel’čuk, I. (2013). Tout ce que nous voulions savoir sur les Phrasèmes, mais… . Cahiers de lexicologie, 102, 129—149.
Google Scholar

Mel’čuk, I. (2020). Clichés and pragmatèmes. Neophilologica, 32, 9—21.
Google Scholar

Mel’čuk, I., & Milićević, J. (2014). Introduction à la linguistique (Vol. 1). Paris, Hermann.
Google Scholar

Mel’čuk, I., & Milićević, J. (2020). An Advanced Introduction to Semantics: A Meaning-Text Approach. Cambridge, Cambridge University Press.
Google Scholar

Melo, G. de, & Paiva, V. de (2014). Sense-Specific Implicative Commitments. In A. Gelbukh (Ed.), CICLing 2014, Part I, LNCS 8403 (pp. 391—402). Berlin — Heidelberg, Springer-Verlag.
Google Scholar

Milićević, J. (2007a). La paraphrase. Modélisation de la paraphrase langagière. Bern, Peter Lang.
Google Scholar

Milićević, J. (2007b). Semantic Equivalence Rules in Meaning-Text Paraphrasing. In L. Wanner (Ed.), Selected Lexical and Grammatical Issues in the Meaning-Text Theory (pp. 263—292). Amsterdam, John Benjamins.
Google Scholar

Milićević, J. (2008). Paraphrase as a Tool for Achieving Lexical Competence in L2. In Proceedings of the Symposium “Complexity, Accuracy and Fluency in Second Language Use, Learning and Teaching” (pp. 153—167). Brussels, Royal Belgium Academy of Science and Arts.
Google Scholar

Mollá, D., & Vicedo, J. L. (2007). Question Answering in Restricted Domains: An Overview. Computational Linguistics, 33(1), 41—61.
Google Scholar

Moon, T., & Erk, K. (2013). An inference-based model of word meaning in context as a paraphrase distribution. ACM Transactions on Intelligent Systems and Technology, 4(3), 1—28.
Google Scholar

Mørdrup, O. (1975). Présuppositions, implications et verbes français. Revue Romane, 10, 125—157.
Google Scholar

Nadathur, P. (2016). Causal necessity and sufficiency in implicativity. In Proceedings of Semantics and Linguistics Theory (SALT) (pp. 1002—1021). Austin, Linguistic Society of America and Cornell Linguistics Circle.
Google Scholar

Nagy T., I., Rácz, A. & Vincze, V. (2020). Detecting light verb constructions across languages. Natural Language Engineering, 26(3), 319—348.
Google Scholar

Nairn, R., Condoravdi, C., & Karttunen, L. (2006). Computing relative polarity for textual inference. In Proceedings of the Fifth International workshop on Inference in Computational Semantics (ICoS-5) (pp. 20—21). Tilburg, Kluwer.
Google Scholar

Norrick, N. R. (1978). Factive adjectives and the theory of factivity. Tubingen, Niemeyer.
Google Scholar

Padó, S., Galley, M., Jurafsky, D., & Manning, C. D. (2009). Robust Machine Translation Evaluation with Entailment Features. In Proceedings of the Fourth Workshop on Statistical Machine Translation (pp. 37—41). Suntec, Association for Computational Linguistics.
Google Scholar

Pap, A. (1955). Strict Implication, Entailment, and Modal Iteration. The Philosophical Review, 64(4), 604—613.
Google Scholar

Parmentier, Y., & Waszczuk, J. (Eds.). (2019). Representation and parsing of multiword expressions: Current trends. Berlin, Language Science Press.
Google Scholar

Petruck, M. R., & Ellsworth, M. (2016). Representing Support Verbs in FrameNet. In Proceedings of the 12th Workshop on Multiword Expressions (pp. 72—77). Berlin, Association for Computational Linguistics.
Google Scholar

Piirainen, E., Filatkina, N., Stumpf, S., & Pfeiffer, Ch. (Eds.). (2020). Formulaic language and new data: Theoretical and methodological implications. Berlin — Boston, De Gruyter.
Google Scholar

Poliak, A., Belinkov, Y., Glass, J., & Durme, B. van (2018). On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language Inference. In Proceedings of the 2018 Conference of the North American (pp. 513—523). New Orleans, Association for Computational Linguistics.
Google Scholar

Pontonx, S. de, & Gross, G. (Dir.). (2004). Lingvisticæ Investigationes, 27(2) : Verbes supports. Nouvel état des lieux. Amsterdam, John Benjamins.
Google Scholar

Pustejovsky, J., Knippen, R., Littman, J. & Sauri, R. (2005). Temporal and event information in natural language text. Language resources and evaluation, 39(2), 123—164.
Google Scholar

Radev, D. R., Hovy, E. H., & McKeown, K. (2002). Introduction to the Special Issue on Summarization. Computational Linguistics, 28, 399—408.
Google Scholar

Ramos, M. A. (2004). Las Construcciones con verbo de apoyo. Madrid, Visor Libros.
Google Scholar

Ramsey, F. P. (1926). Truth and Probability. In R. B. Braithwaite (Ed.), The Foundations of Mathematics and Other Logical Essays (pp. 156—98). London, Routledge and Kegan-Paul Ltd.
Google Scholar

Reichenbach, H. (1949). The Theory of Probability. Berkeley, University of California Press.
Google Scholar

Reichenbach, H. (2006 [1938]). Experience and Prediction: An Analysis of the Foundations and the Structure of Knowledge. Chicago, University of Chicago Press.
Google Scholar

Riezler, S., Vasserman, A., Tsochantaridis, J., Mittal, V., & Liu, Y. (2007). Statistical Machine Translation for Query Expansion in Answer Retrieval. In Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics (pp. 464—471). Prague, Association for Computational Linguistics.
Google Scholar

Rigotti, E., & Greco, S. (2019). Argumentation Library Inference in Argumentation: A Topics-Based Approach to Argument Schemes. Cham, Springer.
Google Scholar

Romeijn, J.-W. (2004). Hypotheses and Inductive Predictions. Synthese, 141(3), 333—364.
Google Scholar

Rudanko, J. (1989). Complementation and Case Grammar. New York, State University of New York Press.
Google Scholar

Rudanko, J. (2002). Complements and Constructions. Corpus-Based Studies on Sentential Complements in English in Recent Centuries. Lanham (Maryland), University of Press of America.
Google Scholar

Rudinger, R., White, A. S., & Durme, B. van (2018). Neural Models of Factuality. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Vol. 1, pp. 731—744). New Orleans, Association for Computational Linguistics.
Google Scholar

Russell, B. (1946). A History of Western Philosophy. London, George Allen and Unwin Ltd.
Google Scholar

Russell, B. (1948). Human Knowledge: Its Scope and Limits. New York, Simon and Schuster.
Google Scholar

Russell, B. (1959). Non-Demonstrative Inference. The Centennial Review of Arts & Science, 3(3), 237—257.
Google Scholar

Sacks, H. (1992). Lectures on Conversation (Vol. 1). Oxford, Blackwell.
Google Scholar

Sag, I. A., Baldwin, T., Bond, F., Copestake, A. A., & Flickinger, D. (2002). Multiword Expressions: A Pain in the Neck for NLP. In Proceedings of Computational Linguistics and Intelligent Text Processing: Third International Conference: CICLing2002, LNCS (pp. 1—15). Berlin, Springer.
Google Scholar

Salmon, W. C. (1963). On Vindicating Induction. Philosophy of Science, 30(3), 252—261.
Google Scholar

Salmon, W. C. (1966). The Foundations of Scientific Inference. Pittsburgh, University of Pittsburgh Press.
Google Scholar

Salmon, W. C. (1981). Rational Prediction. British Journal for the Philosophy of Science, 32(2), 115—125.
Google Scholar

Sanford, D. H. (2003). If P, Then Q: Conditionals and the Foundations of Reasoning (2nd ed.). London — New York, Routledge.
Google Scholar

Saurí, R., & Pustejovsky, J. (2008). From structure to interpretation: A double-layered annotation for event factuality. In The 2nd Linguistic Annotation Workshop, LREC. Marrakech, Association for Computational Linguistics. https://www.researchgate.net/publication/253275884_From_structure_to_interpretation_A_double-layered_annotation_for_event_factuality
Google Scholar

Saurí, R., & Pustejovsky, J. (2009). FactBank: A corpus annotated with event factuality. Language resources and evaluation, 43(3), 227—268.
Google Scholar

Saurí, R., & Pustejovsky, J. (2012). Are you sure that this happened? Assessing the factuality degree of events in text. Computational Linguistics, 38(2), 261—299.
Google Scholar

Savary, A., Ramisch, C., Cordeiro, S., Sangati, F., Vincze, V., Qasemi Zadeh, B., Candito, M., Cap, F., Giouli, V., Stoyanova, I., & Doucet, A. (2017). The PARSEME Shared Task on automatic identification of verbal multiword expressions. In Proceedings of the 13th Workshop onMultiword Expressions, MWE’17 (pp. 31—47). Valencia, Association for Computational Linguistics.
Google Scholar

Savary, A., & Waszczuk, J. (2020). Polish corpus of verbal multiword expressions. In Proceedings of the Joint Workshop on Multiword Expressions and Electronic Lexicons (pp. 32—43). Association for Computational Linguistics.
Google Scholar

Si, Q., Lin, Z., Zheng, M. Y., Fu, P., & Wang, W. (2021). Check It Again: Progressive Visual Question Answering via Visual Entailment. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Vol. 1. Long Papers (pp. 4101—4110). Association for Computational Linguistics.
Google Scholar

Soares, M. A., & Parreiras, F. S. (2020). A literature review on question answering techniques, paradigms and systems. Journal of King Saud University — Computer and Information Sciences, 32(6), 635—646.
Google Scholar

Stenius, E. (1947). Natural Implication and Material Implication. Teoria, 13(2-3), 136—156.
Google Scholar

Sułkowska, M. (2008). Expressions figées dans une perspective multilingue: problèmes d’équivalence et de traduction. Neophilologica, 20, 194—209.
Google Scholar

Tan, K. S., Lim, T. M., Tan, C. W., & Chew, W. W. (2021). Review on Light Verb Constructions in Computational Linguistics. In Conference Proceedings: International Conference on Digital Transformation and Applications (ICDXA 2021) (pp. 153—225). IFERP Explore.
Google Scholar

Torres-Moreno, J. M. (Ed.). (2014). Automatic Text Summarization. Online Library, John Wiley & Sons.
Google Scholar

Traugott, E. C. (2018). Rethinking the Role of Invited Inferencing in Change from the Perspective of Interactional Texts. Open Linguistics, 4, 19—34.
Google Scholar

Trivedi, H., Kwon, H., Khot, T., Sabharwal, A., & Balasubramanian, N. (2019). Repurposing Entailment for Multi-Hop Question Answering Tasks. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) (pp. 2948—2958). Minneaapolis, Association for Computational Linguistics.
Google Scholar

Tutin, A. (2019). Phrases préfabriquées des interactions : quelques observations sur le corpus CLAPI. Cahiers de lexicologie, 114, 63—91.
Google Scholar

Tutin, A., & Grossmann, Fr. (2002). Collocations régulières et irrégulières : esquisse de typologie du phénomène collocatif. Revue Française de Linguistique Appliquée, 7(1), 7—25.
Google Scholar

Vetulani, G. (2012). Kolokacje werbo-nominalne jako samodzielne jednostki języka. Syntak­tyczny słownik kolokacji werbo-nominalnych na potrzeby zastosowań informatycznych. Część I. Poznań, Wydawnictwo Naukowe UAM.
Google Scholar

Vila, M., Martí, M. A., & Rodríguez, H. (2014). Is This a Paraphrase? What Kind? Paraphrase Boundaries and Typology. Open Journal of Modern Linguistics, 4, 205—218.
Google Scholar

Vincze, V., Nagy T., I., & Berend, G. (2011). Detecting noun compounds and light verb constructions: a contrastive study. In Proceedings of the Workshop on Multiword Expressions: from Parsing and Generation to the Real World (MWE 2011) (pp. 116—121). Portland, Association for Computational Linguistics.
Google Scholar

Vivès, R. (1993). La prédication nominale et l’analyse par verbes supports. L’Information grammaticale, 59, 8—15.
Google Scholar

Wanner, L. (Ed.). (1996). Lexical functions in lexicography and natural language processing. Amsterdam — Philadelphia, John Benjamins.
Google Scholar

White, A. S. (2014). Factive-implicatives and modalized complements. In Proceedings of the 44th annual meeting of the North East Linguistic Society (NELS) (pp. 267—278). Amherst, Association for Computational Linguistics.
Google Scholar

White, A. S. (2020). Lexically Triggered Veridicality Inferences. Handbook of Pragmatics, 22, 115—148.
Google Scholar

White, A. S. (2021). On believing and hoping whether. Semantics & Pragmatics, 14(6). Early access version. https://doi.org/10.3765/sp.14.6
Google Scholar

White, A. S., & Rawlins, K. (2018). The Role of Veridicality and Factivity in Clause Selection. In Proceedings of the 48th Annual Meeting of the North East Linguistic Society (pp. 221—234). Amherst, GLSA Publications.
Google Scholar

White, A. S., Rudinger, R., Rawlins, K., & Durme, B. van (2018). Lexicosyntactic Inference in Neural Models. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (pp. 4717—4724). Brussels, Association for Computational Linguistics.
Google Scholar

Wood, D. (2015). Fundamentals of Formulaic Language. An Introduction. Bloomsbury Academic.
Google Scholar

Wood, M. M. (1986). A definition of idiom. Bloomington, Indiana University Linguistics Club.
Google Scholar

Wray, A. (2002). Formulaic Language and the Lexicon. Cambridge, Cambridge University Press.
Google Scholar

Wray, A. (2008). Formulaic language: Pushing the boundaries. Oxford, Oxford University Press.
Google Scholar

Wray, A., & Perkins, M. R. (2000). The functions of formulaic language: An integrated model. Language and Communication, 20, 1—28.
Google Scholar

Yang, M., Liu, Y., & Mayuranath, R. (2020). Training and Inference Methods for High-Coverage Neural Machine Translation. In Proceedings of the 4th Workshop on Neural Generation and Translation (WNGT 2020) (pp. 119—128). Association for Computational Linguistics.
Google Scholar

Yao, J., Wan, X., & Xiao, J. (2017). Recent advances in document summarization. Knowledge and Information Systems, 53, 297—336.
Google Scholar

Yoshinaka, M., Kajiwara, T., & Arase, Y. (2020). SAPPHIRE: Simple aligner for phrasal paraphrase with hierarchical representation. In LREC 2020 — 12th International Conference on Language Resources and Evaluation, Conference Proceedings (pp. 6861—6866). Marseille, European Language Resources Association.
Google Scholar

Zaenen, A., & Karttunen, L. (2013). Veridicity annotation in the lexicon? A look at factive adjectives. In Proceedings of the 9th Joint ISO — ACL SIGSEM Workshop on Interoperable Semantic Annotation (pp. 51—58). Potsdam, Association for Computational Linguistics.
Google Scholar

Zaenen, A., Karttunen, L., & Crouch, R. (2005). Local textual inference: Can it be defined or circumscribed? In Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment (pp. 31—36). Michigan, Ann Arbor.
Google Scholar

Zhou, L., Lin, C., & Hovy, E. H. (2006). Re-evaluating Machine Translation Results with Paraphrase Support. In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (pp. 77—84). Sydney, Association for Computational Linguistics.
Google Scholar

Zhou, Y., Hu, X., & Chung, V. (2022). Automatic Construction of Fine-Grained Paraphrase Corpora System Using Language Inference. Applied Sciences, 12(1): 499, 1—16.
Google Scholar

Zuber, R. (1972). Structure présuppositionnelle du langage. Dunod, Paris.
Google Scholar