| Challenge: | a large dataset of zero pronouns has been constructed to identify adjunct zero anaphoras . a lack of a dataset covering them has limited our ability to annotate them exhaustively . |
| Approach: | They propose to annotate adjuncts marked by -de in Japanese and a second scheme to annnotate them in a more direct manner. |
| Outcome: | The proposed annotation schemes are more accurate than the first one. |
Similar Papers
A Gold Anaphora Annotation Layer on an Eye Movement Corpus (L18-1)
Copied to clipboard
| Challenge: | Anaphora resolution is a complex process in which multiple linguistic factors play a role. |
| Approach: | They used annotated anaphorical pronouns from newspaper articles read by humans to model reading time of pronounes. |
| Outcome: | The proposed resource allows to study human anaphora resolution on natural data. |
Universal Anaphora: The First Three Years (2024.lrec-main)
Copied to clipboard
Massimo Poesio, Maciej Ogrodniczuk, Vincent Ng, Sameer Pradhan, Juntao Yu, Nafise Sadat Moosavi, Silviu Paun, Amir Zeldes, Anna Nedoluzhko, Michal Novák, Martin Popel, Zdeněk Žabokrtský, Daniel Zeman
| Challenge: | Universal Anaphora initiative aims to push forward the state of the art in anaphora and anaphorism resolution by expanding the aspects of anaphonic interpretation which are or can be reliably annotated in an anagraphic corpora. |
| Approach: | They propose to develop a standard for anaphoric annotations and a method for evaluating models that can carry out this type of interpretation. |
| Outcome: | The Universal Anaphora initiative aims to push forward the state of the art in anaphora and anaphorism resolution by producing unified standards to annotate and encode annotations, delivering datasets encoded according to these standards, and developing methods for evaluating models that carry out this type of interpretation. |
Bridging Anaphora Resolution as Question Answering (2020.acl-main)
Copied to clipboard
| Challenge: | Existing studies on bridging anaphora resolution focus on question answering based on context . briding anaphorisms and their antecedents are linked via various lexico-semantic, frame or encyclopedic relations. |
| Approach: | They propose a question answering framework for bridging anaphora resolution . they propose briding anaphorisms and their antecedents are linked via various lexico-semantic, frame or encyclopedic relations. |
| Outcome: | The proposed method generates state-of-the-art results on two bridging corpora. |
A Methodology for Creating Question Answering Corpora Using Inverse Data Annotation (2020.acl-main)
Copied to clipboard
Jan Deriu, Katsiaryna Mlynchyk, Philippe Schläpfer, Alvaro Rodrigo, Dirk von Grünigen, Nicolas Kaiser, Kurt Stockinger, Eneko Agirre, Mark Cieliebak
| Challenge: | Existing methods to efficiently construct corpus for question answering over structured data are time-consuming and cost-intensive. |
| Approach: | They propose a method to efficiently construct a corpus for question answering over structured data. |
| Outcome: | The proposed method triples the annotation speed while maintaining complexity of queries. |
Learning a Cost-Effective Annotation Policy for Question Answering (2020.emnlp-main)
Copied to clipboard
| Challenge: | State-of-the-art question answering systems require large amounts of training data for which labeling is time consuming and thus expensive. |
| Approach: | They propose a framework for annotating QA datasets that entails learning a cost-effective annotation policy and a semi-supervised annotation scheme. |
| Outcome: | The proposed approach can reduce up to 21.1% of the annotation cost compared with traditional methods . the proposed approach is based on a cost-effective annotation policy and semi-supervised annotation scheme . |
Zero Pronoun Resolution with Attention-based Neural Network (C18-1)
Copied to clipboard
| Challenge: | Recent neural network methods for zero pronoun resolution use contextual information to encode the zero pronomins since they contain no actual content. |
| Approach: | They propose a self-attention mechanism for encoding zero pronouns that focus on some informative parts of the associated texts and produce an efficient way of encode them. |
| Outcome: | The proposed model significantly surpasses existing Chinese zero pronoun resolution baseline systems. |
TIGQA: An Expert-Annotated Question-Answering Dataset in Tigrinya (2024.lrec-main)
Copied to clipboard
| Challenge: | Existing annotated datasets for NLP tasks in languages with limited resources are limited. |
| Approach: | They propose to use machine translation to convert existing Tigrinya dataset into a Tigrina dataset in SQuAD format. |
| Outcome: | The proposed dataset is an expert-annotated Tigrinya dataset with 2,685 question-answer pairs covering 122 diverse topics. |
Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering (2021.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods to improve Question Answering performance on non-English data are expensive and limited to evaluation set. |
| Approach: | They propose a method to improve Question Answering performance without additional annotations by leveraging Question Generation models to produce synthetic samples in a cross-lingual fashion. |
| Outcome: | The proposed method outperforms baselines on four datasets in English significantly . the proposed model outperformed baselines in english and is comparable to the validation set of the original SQuAD. |
JDocQA: Japanese Document Question Answering Dataset for Generative Language Models (2024.lrec-main)
Copied to clipboard
| Challenge: | Document question answering is a task of question answering on given documents such as reports, slides, pamphlets, and websites. |
| Approach: | They propose a large-scale document-based QA dataset that requires both visual and textual information to answer questions. |
| Outcome: | The proposed dataset incorporates multiple categories of questions and unanswerable questions from the document for realistic question-answering applications. |
Improving Unsupervised Question Answering via Summarization-Informed Question Generation (2021.emnlp-main)
Copied to clipboard
| Challenge: | Question Generation (QG) is the production of meaningful questions given a set of input passages and corresponding answers. |
| Approach: | They propose a method which uses questions generated heuristically from news summaries as a source of training data for a QG system. |
| Outcome: | The proposed method outperforms previous unsupervised models on three in-domain datasets and three out-of-domain ones. |