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Benchmarking Answer Verification Methods for Question Answering-Based Summarization Evaluation Metrics ...
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Question-Based Salient Span Selection for More Controllable Text Summarization ...
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Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies ...
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ESTER: A Machine Reading Comprehension Dataset for Reasoning about Event Semantic Relations ...
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What is Your Article Based On? Inferring Fine-grained Provenance ...
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BabyBERTa: Learning More Grammar With Small-Scale Child-Directed Language ...
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{Z}ero-shot {L}abel-Aware {E}vent {T}rigger and {A}rgument {C}lassification ...
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Zero-shot Event Extraction via Transfer Learning: Challenges and Insights ...
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Do We Know What We Don't Know? Studying Unanswerable Questions beyond SQuAD 2.0 ...
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Towards Question-Answering as an Automatic Metric for Evaluating the Content Quality of a Summary ...
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Constrained Labeled Data Generation for Low-Resource Named Entity Recognition ...
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Abstract:
Read paper: https://www.aclanthology.org/2021.findings-acl.396 Abstract: Named Entity Recognition (NER) in low-resource languages has been a long-standing challenge in NLP. Recent work has shown great progress in two directions: developing cross-lingual features/models to transfer knowledge to low-resource languages, and translating source-language training data into low-resource target-language training data by projecting annotations with cheap resources. We focus on the second direction in this study. Existing methods suffer from the low quality of the resulting annotated data in the target language; for example, they cannot handle word order and lexical ambiguity well. To handle these limitations we propose a novel approach that uses the projected annotation to generate pseudo supervised data with a transformer language model and a constrained beam search. This allows us to generate more diverse, higher quality, as well as higher quantities of annotated data in the target language. Experiments demonstrate ...
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Keyword:
Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Neural Network; Semantics
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URL: https://dx.doi.org/10.48448/v7dc-hk16 https://underline.io/lecture/26487-constrained-labeled-data-generation-for-low-resource-named-entity-recognition
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Cross-lingual Entity Alignment with Incidental Supervision ...
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TransOMCS: From Linguistic Graphs to Commonsense Knowledge ...
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Is Killed More Significant than Fled? A Contextual Model for Salient Event Detection ...
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Towards Question-Answering as an Automatic Metric for Evaluating the Content Quality of a Summary ...
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Extending Wikification: Nominal discovery, nominal linking, and the grounding of nouns
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