| 1. |
- Bernardy, Jean-Philippe, 1978, et al.
(författare)
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A Computational Treatment of Anaphora and its Algorithmic Implementation
- 2021
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Ingår i: Journal of Logic, Language and Information. - : Springer Science and Business Media LLC. - 0925-8531 .- 1572-9583. ; 30, s. 1-29
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we propose a framework capable of dealing with anaphora and ellipsis which is both general and algorithmic. This generality is ensured by the compination of two general ideas. First, we use a dynamic semantics which reperent effects using a monad structure. Second we treat scopes flexibly, extending them as needed. We additionally implement this framework as an algorithm which translates abstract syntax to logical formulas. We argue that this framework can provide a unified account of a large number of anaphoric phenomena. Specifically, we show its effectiveness in dealing with pronominal and VP-anaphora, strict and lazy pronouns, lazy identity, bound variable anaphora, e-type pronouns, and cataphora. This means that in particular we can handle complex cases like Bach-Peters sentences, which require an account dealing simultaneously with several phenomena. We use Haskell as a meta-language to present the theory, which also consitutes an implementation of all the phenomena discussed in the paper. To demonstrate coverage, we propose a test suite that can be used to evaluate computational approaches to anaphora.
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| 2. |
- Bernardy, Jean-Philippe, 1978, et al.
(författare)
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A Logic with Measurable Spaces for Natural Language Semantics
- 2019
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Ingår i: TbiLLC 2019: Thirteenth International Tbilisi Symposium on Language, Logic and Computation,16-20 September 2019..
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We present a Logic with Measurable Spaces (LMS) and argue that it is suitable to represent the semantics of many natural language phenomena. LMS draws inspiration from several sources. It is decidable (like description logics). It features Sigma spaces (like Martin-Löf type-theory). It internalises the notion of the cardinality (in fact, here, measures) of spaces and ratios thereof, allowing to capture the notion of event probability. In addition, LMS is arguably a concise system. Thanks to all these qualities, we hope that LMS can play a role in the foundations of natural language semantics.
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| 3. |
- Bernardy, Jean-Philippe, 1978, et al.
(författare)
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A logic with measurable spaces for natural language semantics
- 2020
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Ingår i: Applied Mathematics, Informatics And Mechanics. - 1512-0074. ; 2020, s. 31-44
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- We present a Logic with Measurable Spaces (LMS) and argue that it is suitable to represent the semantics of a number of natural lan- guage phenomena. LMS draws inspiration from several sources. It is decidable (like descriptive logics). It features Sigma spaces (like Martin-Lf type-theory). It internalises the notion of the cardinality (in fact, here, measures) of spaces and ratios thereof, allow- ing to capture the notion of event probability. In addition to being a powerful system, it is also concise and has a precise semantics in terms of integrals. Thanks to all these qualities, we hope that LMS can play a role in the foundations of natural language semantics.
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| 4. |
- Bernardy, Jean-Philippe, 1978, et al.
(författare)
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Bayesian Inference Semantics: A Modelling System and A Test Suite
- 2019
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Ingår i: Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM), 6-7 June 2019, Minneapolis, Minnesota, USA / Rada Mihalcea, Ekaterina Shutova, Lun-Wei Ku, Kilian Evang, Soujanya Poria (Editors). - Stroudsburg, PA : Association for Computational Linguistics. - 9781948087933
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Konferensbidrag (refereegranskat)abstract
- We present BIS, a Bayesian Inference Semantics, for probabilistic reasoning in natural language. The current system is based on the framework of Bernardy et al. (2018), but departs from it in important respects. BIS makes use of Bayesian learning for inferring a hypothesis from premises. This involves estimating the probability of the hypothesis, given the data supplied by the premises of an argument. It uses a syntactic parser to generate typed syntactic structures that serve as input to a model generation system. Sentences are interpreted compositionally to probabilistic programs, and the corresponding truth values are estimated using sampling methods. BIS successfully deals with various probabilistic semantic phenomena, including frequency adverbs, generalised quantifiers, generics, and vague predicates. It performs well on a number of interesting probabilistic reasoning tasks. It also sustains most classically valid inferences (instantiation, de Morgan’s laws, etc.). To test BIS we have built an experimental test suite with examples of a range of probabilistic and classical inference patterns.
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| 5. |
- Bernardy, Jean-Philippe, 1978, et al.
(författare)
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Bayesian Inference Semantics for Natural Language
- 2022
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Ingår i: Probabilistic Approaches to Linguistic Theory / edited by Jean-Philippe Bernardy, Rasmus Blanck, Stergios Chatzikyriakidis, Shalom Lappin, Aleksandre Maskharashvili.. - Stanford : CSLI Publications. - 9781684000791 ; , s. 161-228
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Bokkapitel (refereegranskat)abstract
- We present a Bayesian Inference Semantics for natural language, which computes the probability conditions of sentences compositionally, through semantic functions matching with the types of their syntactic constituents. This system captures the vagueness of classifier terms and scalar modifiers. It also offers a straightforward treatment of the sorites paradox. Our framework expresses probabilistic inferences, which rely on lexically encoded priors, and it captures the effect of informational update on these inferences, through Bayesian modelling. The central device with which we represent probabilistic interpretation is the assignment of measurable spaces to objects and properties. We estimate the probability of a predication by measuring the density of relevant objects in the space of the property that the predicate denotes. We explore two alternative models for the priors. The first one is based on Gaussian distributions, but it exhibits computational intractability with some cases of Monte Carlo sampling. The second is based on uniform densities, and in a number of important instances, it allows us to avoid Monte Carlo sampling. We construct a test suite to illustrate the range of syntactic and semantic constructions, and the inference types, that our system covers.
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| 6. |
- Bernardy, Jean-Philippe, 1978, et al.
(författare)
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Predicates as Boxes in Bayesian Semantics for Natural Language
- 2019
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Ingår i: Proceedings of the 22nd Nordic Conference on Computational Linguistics (NoDaLiDa 2019), 30 September-2 October, 2019, Turku, Finland / Mareike Hartmann, Barbara Plank (Editors). - Linköping : Linköping University Electronic Press. - 1650-3686 .- 1650-3740. - 9789179299958
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Konferensbidrag (refereegranskat)abstract
- In this paper, we present a Bayesian approach to natural language semantics. Our main focus is on the inference task in an environment where judgments require probabilistic reasoning. We treat nouns, verbs, adjectives, etc. as unary predicates, and we model them as boxes in a bounded domain. We apply Bayesian learning to satisfy constraints expressed as premises. In this way we construct a model, by specifying boxes for the predicates. The probability of the hypothesis (the conclusion) is evaluated against the model that incorporates the premises as constraints.
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| 7. |
- Bernardy, Jean-Philippe, 1978, et al.
(författare)
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Two experiments for embedding Wordnet hierarchy into vector spaces
- 2019
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Ingår i: Fellbaum, Christiane; Vossen, Piek; Rudnicka, Ewa; et al., 2019, Proceedings of the 10th Global WordNet Conference, July 23–27, 2019, Wrocław, Poland. - Wrocław : Oficyna Wydawnicza Politechniki Wrocławskiej. - 9788374931083
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Konferensbidrag (refereegranskat)
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| 8. |
- Blanck, Rasmus, 1982, et al.
(författare)
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From TAG to HOL Representations of AMRs via ACGs
- 2018
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Ingår i: Proceedings of the Symposium on Logic and Algorithms in Computational Linguistics 2018. Stockholm, 28–31 August 2018 / Krasimir Angelov, Kristina Liefke, Roussanka Loukanova, Michael Moortgat, Satoshi Tojo (eds.). - Stockholm : Stockholm University, DiVA portal for digital publications.
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Konferensbidrag (refereegranskat)abstract
- We investigate the possibility of constructing an Abstract Categorial Grammar (ACG) that relates Tree Adjoining Grammar (TAG) and Higher Order Logic (HOL) formulas encoding Abstract Meaning Representations (AMRs). We also propose another ACG that relates TAG and HOL formulas expressing the neo-Davidsonian event semantics. Both of these encodings are based on the already existing ACG encoding of the syntax-semantics interface where TAG derivations are interpreted as HOL formulas representing Montague semantics. In particular, both of these encodings share the same abstract language coming from the ACG encoding of TAG with Montague semantics, which is second-order. For second-order ACGs, problems of parsing and generation are known to be of polynomial complexity. Thus we get the natural language generation and parsing with TAGs and HOL formulas modeling AMR for free.
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| 9. |
- Blanck, Rasmus, 1982, et al.
(författare)
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From Tree Adjoining Grammars to Higher Order Representations of Abstract Meaning Representations via Abstract Categorial Grammars
- 2020
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Ingår i: Loukanova R. (eds) Logic and Algorithms in Computational Linguistics 2018 (LACompLing2018). Studies in Computational Intelligence, vol 860.. - Cham : Springer. - 1860-949X .- 1860-9503. - 9783030300760
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Konferensbidrag (refereegranskat)abstract
- We construct an Abstract Categorial Grammar (ACG) that interrelates Tree Adjoining Grammar (TAG) and Higher Order Logic (HOL) formulas encoding Abstract Meaning Representations (AMRs). We also propose another ACG that interrelates TAG and HOL formulas expressing neo-Davidsonian event semantics. Both of these encodings are based on the already existing ACG encoding of the syntax– semantics interface where TAG derivations are interpreted as HOL formulas representing Montague semantics. In particular, both of these encodings share the same abstract language coming from the ACG encoding of TAG with Montague semantics, which is second-order. For second-order ACGs, problems of parsing and generation are known to be of polynomial complexity. Thus we get the natural language generation and parsing with TAGs and HOL formulas modelling AMRs for free.
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| 10. |
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Probabilistic Approaches to Linguistic Theory
- 2022
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Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- During the last two decades, computational linguists, in concert with other researchers in AI, have turned to machine learning and statistical techniques to capture features of natural language and aspects of the learning process that are not easily accommodated in classical algebraic frameworks. These developments are producing a revolution in linguistics in which traditional symbolic systems are giving way to probabilistic and deep learning approaches. This collection features articles that provide background to these approaches, and their application in syntax, semantics, pragmatics, morphology, psycholinguistics, neurolinguistics, and dialogue modeling. Each chapter provides a self-contained introduction to the topic that it covers, making this volume accessible to graduate students and researchers in linguistics, NLP, AI, and cognitive science.
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