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1
Dependency Patterns of Complex Sentences and Semantic Disambiguation for Abstract Meaning Representation Parsing ...
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2
One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets ...
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3
Modeling Sense Structure in Word Usage Graphs with the Weighted Stochastic Block Model ...
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4
InFillmore: Frame-Guided Language Generation with Bidirectional Context ...
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5
Overcoming Poor Word Embeddings with Word Definitions ...
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6
Learning Embeddings for Rare Words Leveraging Internet Search Engine and Spatial Location Relationships ...
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7
Evaluating Universal Dependency Parser Recovery of Predicate Argument Structure via CompChain Analysis ...
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8
ParsFEVER : a Dataset for Farsi Fact Extraction and Verification ...
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9
Did the Cat Drink the Coffee? Challenging Transformers with Generalized Event Knowledge ...
Abstract: Prior research has explored the ability of computational models to predict a word semantic fit with a given predicate. While much work has been devoted to modeling the typicality relation between verbs and arguments in isolation, in this paper we take a broader perspective by assessing whether and to what extent computational approaches have access to the information about the typicality of entire events and situations described in language (Generalized Event Knowledge). Given the recent success of Transformers Language Models (TLMs), we decided to test them on a benchmark for the dynamic estimation of thematic fit. The evaluation of these models was performed in comparison with SDM, a framework specifically designed to integrate events in sentence meaning representations, and we conducted a detailed error analysis to investigate which factors affect their behavior. Our results show that TLMs can reach performances that are comparable to those achieved by SDM. However, additional analysis consistently ...
Keyword: Computational Algorithm; Computational Linguistics; Data Management System; FOS Languages and literature; Linguistics; Natural Language Processing; Semantics
URL: https://dx.doi.org/10.48448/6xfs-sx93
https://underline.io/lecture/29800-did-the-cat-drink-the-coffeequestion-challenging-transformers-with-generalized-event-knowledge
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10
Script Parsing with Hierarchical Sequence Modelling ...
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11
Teach the Rules, Provide the Facts: Targeted Relational-knowledge Enhancement for Textual Inference ...
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12
Multilingual Neural Semantic Parsing for Low-Resourced Languages ...
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13
Inducing Language-Agnostic Multilingual Representations ...
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14
Denoising Word Embeddings by Averaging in a Shared Space ...
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15
Semantic shift in social networks ...
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16
Evaluating a Joint Training Approach for Learning Cross-lingual Embeddings with Sub-word Information without Parallel Corpora on Lower-resource Languages ...
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17
NUS-IDS at CASE 2021 Task 1: Improving Multilingual Event Sentence Coreference Identification with Linguistic Information ...
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18
Can Transformer Langauge Models Predict Psychometric Properties? ...
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