The UIR Uncertainty Corpus for Chinese: Annotating Chinese Microblog Corpus for Uncertainty Identification from Social Media (L18-1)
Copied to clipboard
| Challenge: | Uncertainty identification is an important semantic processing task, critical to the quality of information in terms of factuality in many NLP techniques and applications. |
| Approach: | They propose to annotate Chinese microblogs with an open uncertainty corpus . they propose to use contextual uncertain semantics rather than traditional cue-phrases to identify uncertainty . |
| Outcome: | The proposed corpus can be used to identify uncertainty in social media texts. |
Similar Papers
Do you Feel Certain about your Annotation? A Web-based Semantic Frame Annotation Tool Considering Annotators’ Concerns and Behaviors (2020.lrec-1)
Copied to clipboard
| Challenge: | Existing tools for manual annotations are resourceintensive and complex, and experienced annotators and tools specialized for the purpose of the annotation task are required. |
| Approach: | They propose to use a web-based application with a responsive design for modular semantic frame annotation (SFA) the proposed application keeps track of the time and changes during the annotation process and stores the users’ confidence with the current annotation. |
| Outcome: | The proposed system can be used to build a manually annotated corpus and its arguments for task 2 of SemEval 2019 regarding unsupervised lexical frame induction. |
An Event-comment Social Media Corpus for Implicit Emotion Analysis (2020.lrec-1)
Copied to clipboard
| Challenge: | Existing methods for identifying implicit emotions have been poor in analyzing explicit emotions. |
| Approach: | They propose to construct a Chinese eventcomment social media emotion corpus which deals with both explicit and implicit emotions with more emphasis being placed on the implicit ones. |
| Outcome: | The proposed corpus will be useful for both explicit and implicit emotion classification and detection as well as event classification. |
The Multilingual Microblog Translation Corpus: Improving and Evaluating Translation of User-Generated Text (2022.lrec-1)
Copied to clipboard
| Challenge: | a corpus of over 200,000 microblog translations supports translation of thirteen languages into English . large collections of parallel text, or bitext, are increasingly available in many languages . |
| Approach: | They propose a corpus of over 200,000 microblog posts that supports translation of thirteen languages into English. |
| Outcome: | The proposed corpus contains over 200,000 translations of microblog posts in 13 languages . fine-tuning showed significant improvements in translation quality . |
M-CNER: A Corpus for Chinese Named Entity Recognition in Multi-Domains (L18-1)
Copied to clipboard
| Challenge: | NER is one of the most important natural language processing tasks. |
| Approach: | They propose to annotate sentences from human-computer interaction, social media, and e-commerce using two rounds of annotation. |
| Outcome: | The proposed system performs the best on all the data sets. |
Fluid Annotation: A Granularity-aware Annotation Tool for Chinese Word Fluidity (L18-1)
Copied to clipboard
| Challenge: | Using word segmentation, we propose a wordhood annotation framework for Chinese language . word segmentations have been used for years in preprocessing NLP tasks for languages without explicit word delimiter. |
| Approach: | They propose a word-granularity-aware annotation framework for Chinese language . they argue that word segmentation is fluid in nature and that it rearranges the boundary of word segmentations and linguistic annotation. |
| Outcome: | The proposed framework rearranges the boundary between word segmentation and linguistic annotation and supports flexible annotation tasks for various linguistic and affective phenomena. |
Target-based Sentiment Annotation in Chinese Financial News (2020.lrec-1)
Copied to clipboard
| Challenge: | Using a large corpus of 8,314 target-level sentiment annotations, sentiment classification on multiple opinion aspects/targets level is unsatisfactory. |
| Approach: | They propose to construct a large-scale target-based sentiment annotation corpus on Chinese financial news text. |
| Outcome: | The proposed corpus has 8,314 target-level sentiment annotations on Chinese financial news text. |
On the Idiosyncrasies of the Mandarin Chinese Classifier System (N19-1)
Copied to clipboard
| Challenge: | idiosyncrasies of the Chinese classifier system have been studied, but little work has been done to quantify them with statistical methods. |
| Approach: | They propose an information-theoretic approach to measuring idiosyncrasies in Mandarin Chinese by calculating the mutual information between the distribution over classifiers and distributions over other linguistic quantities. |
| Outcome: | The proposed method reduces uncertainty in Mandarin Chinese classifiers by knowing semantic information about nouns that they modify. |
“None of the Above”: Measure Uncertainty in Dialog Response Retrieval (2020.acl-main)
Copied to clipboard
| Challenge: | End-to-end (E2E) dialog retrieval models jointly encode a dialog and a candidate response, assuming the ground truth is always present in the candidate set. |
| Approach: | They propose to capture the original retrieval model's confidence concerning the best prediction using trivial additional computation. |
| Outcome: | The proposed model can capture the model's confidence concerning the best prediction using trivial additional computation. |
Leveraging Social Context for Humor Recognition and Sense of Humor Evaluation in Social Media with a New Chinese Humor Corpus - HumorWB (2024.lrec-main)
Copied to clipboard
| Challenge: | Existing humor computing research focuses on content while neglecting interaction relationships in social media. |
| Approach: | They propose a dataset which introduces social context information from social media . they propose 'humor recognition' task and 'horror evaluation task' |
| Outcome: | The proposed model incorporates social context information from social media . it shows that it is efficient and can be used to evaluate humor in real life . |
UOREX: Towards Uncertainty-Aware Open Relation Extraction (2025.naacl-long)
Copied to clipboard
| Challenge: | Existing methods for relation extraction are limited by their inability to accurately self-assess their performance. |
| Approach: | They propose an approach that effectively models a part of the epistemic uncertainty within OpenRE by preventing overconfident errors. |
| Outcome: | The proposed approach improves OpenRE reliability by preventing overconfident errors. |