Papers with Chinese corpus
HL-EncDec: A Hybrid-Level Encoder-Decoder for Neural Response Generation (C18-1)
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| Challenge: | Existing models for conversation systems operate sentences at word-level . word-based models suffer from Unknown Words Issue and Preference Issue . |
| Approach: | They propose a hybrid-level Encoder-Decoder model which utilizes word-level features and character-level ones. |
| Outcome: | The proposed model outperforms non-word-level models in automatic metrics and human annotations on a Chinese corpus. |
TED-CDB: A Large-Scale Chinese Discourse Relation Dataset on TED Talks (2020.emnlp-main)
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| Challenge: | TED-CDB dataset is a unique corpus of spoken discourse in Chinese . TED is based on the concept that discourse relations are grounded in an identifiable set of discourse connectives or Altlex expressions. |
| Approach: | They have created a dataset that annotates TED talks in Chinese . they propose to adapt the dataset to Chinese news text to improve its performance . |
| Outcome: | The TED-CDB dataset can improve the performance of systems for languages other than Chinese . it is adapted to features that are not present in English and can extract discourse semantic features . |
CLEEK: A Chinese Long-text Corpus for Entity Linking (2020.lrec-1)
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| Challenge: | Entity linking is a fundamental task in natural language processing, says nigel kilgstrom . existing corpora for entity linking in china are lacking and deficient, he says . kilsmstrom: a new method for entity disambiguation can be developed for Chinese . |
| Approach: | They build a Chinese corpus of multi-domain long text for entity linking . they evaluate the difficulty of documents with respect to entity linking using a measure . |
| Outcome: | The proposed corpus is based on 100 documents from diverse domains and is publicly accessible. |
ConFiguRe: Exploring Discourse-level Chinese Figures of Speech (2022.coling-1)
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| Challenge: | Figures of speech often deviate from their literal meanings to express deeper semantic implications. |
| Approach: | They propose a concept of figurative unit, which is the carrier of a figure, and build a Chinese corpus for Contextualized Figure Recognition. |
| Outcome: | The proposed model is based on 12 types of figures commonly used in Chinese . it shows that the proposed tasks are challenging for existing models . |
CSL: A Large-scale Chinese Scientific Literature Dataset (2022.coling-1)
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| Challenge: | Existing datasets centered around the English language restrict development of Chinese scientific NLP. |
| Approach: | They present a large-scale Chinese scientific literature dataset based on Chinese papers . they use semi-structured data as a natural annotation for many supervised NLP tasks . |
| Outcome: | The proposed dataset can serve as a Chinese corpus and perform many supervised tasks. |
The BQ Corpus: A Large-scale Domain-specific Chinese Corpus For Sentence Semantic Equivalence Identification (D18-1)
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| Challenge: | Bank Question corpus is a corpus for sentence semantic equivalence identification (SSEI) because of rich expressions in natural languages, SSEI is really a challenging task. |
| Approach: | They propose to cluster 120,000 question pairs from 1-year online bank custom service logs into stacks by the Word Mover’s Distance (WMD) based Affinity Propagation algorithm to achieve questions with the same intent. |
| Outcome: | The proposed method achieves questions with the same intent by clustering deduplicated questions into stacks by the Word Mover’s Distance (WMD) based Affinity Propagation (AP) algorithm. |
A Corpus of Adpositional Supersenses for Mandarin Chinese (2020.lrec-1)
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| Challenge: | Adpositions are frequent markers of semantic relations, but they are highly ambiguous and vary significantly from language to language. |
| Approach: | They propose to annotate Chinese adpositions in a corpus with all aforementioned supersenses . they adapt a framework that defined a set of supersens according to ostensibly language-independent criteria . |
| Outcome: | The proposed corpus is the first to be broadly annotated with adposition semantics in Chinese . it shows that the supersense categories are well-suited to Chinese adepositions despite syntactic differences from English . |
A Simple Yet Effective Corpus Construction Method for Chinese Sentence Compression (2022.lrec-1)
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| Challenge: | Deletion-based sentence compression has made significant progress in the english language . however, there is a lack of large-scale and high-quality parallel corpus for the Chinese language to train an efficient system. |
| Approach: | They propose to construct a Chinese corpus with 151k pairs of sentences and train extractive and generative neural compression models on the constructed corpus. |
| Outcome: | The proposed method generates high-quality compressed sentences on automatic and human evaluation metrics compared with baselines. |