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Automatic Error Type Annotation for Arabic ...
Abstract: We present ARETA, an automatic error type annotation system for Modern Standard Arabic. We design ARETA to address Arabic’s morphological richness and orthographic ambiguity. We base our error taxonomy on the Arabic Learner Corpus (ALC) Error Tagset with some modifications. ARETA achieves a performance of 85.8% (micro average F1 score) on a manually annotated blind test portion of ALC. We also demonstrate ARETA’s usability by applying it to a number of submissions from the QALB 2014 shared task for Arabic grammatical error correction. The resulting analyses give helpful insights on the strengths and weaknesses of different submissions, which is more useful than the opaque M2 scoring metrics used in the shared task. ARETA employs a large Arabic morphological analyzer but is completely unsupervised otherwise. We make ARETA publicly available. ...
Keyword: Computational Linguistics; Information Extraction; Language Models; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
URL: https://dx.doi.org/10.48448/1s26-nw85
https://underline.io/lecture/39891-automatic-error-type-annotation-for-arabic
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Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training ...
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HittER: Hierarchical Transformers for Knowledge Graph Embeddings ...
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AttentionRank: Unsupervised Keyphrase Extraction using Self and Cross Attentions ...
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Corpus-based Open-Domain Event Type Induction ...
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Extracting Event Temporal Relations via Hyperbolic Geometry ...
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Partially Supervised Named Entity Recognition via the Expected Entity Ratio Loss ...
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Honey or Poison? Solving the Trigger Curse in Few-shot Event Detection via Causal Intervention ...
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Corrected CBOW Performs as well as Skip-gram ...
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An Empirical Study on Multiple Information Sources for Zero-Shot Fine-Grained Entity Typing ...
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Logic-level Evidence Retrieval and Graph-based Verification Network for Table-based Fact Verification ...
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ChemNER: Fine-Grained Chemistry Named Entity Recognition with Ontology-Guided Distant Supervision ...
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Unsupervised Keyphrase Extraction by Jointly Modeling Local and Global Context ...
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TEET! Tunisian Dataset for Toxic Speech Detection ...
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Entity Relation Extraction as Dependency Parsing in Visually Rich Documents ...
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MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations ...
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Lifelong Event Detection with Knowledge Transfer ...
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SUBSUME: A Dataset for Subjective Summary Extraction from Wikipedia Documents ...
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Few-Shot Named Entity Recognition: An Empirical Baseline Study ...
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Low-resource Taxonomy Enrichment with Pretrained Language Models ...
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