| Challenge: | Existing approaches to generating semantic annotations for different languages are attracting more and more interest. |
| Approach: | They propose to extend Universal Semantic Tagging to Mandarin Chinese and evaluate its performance. |
| Outcome: | The proposed scheme is only tested in four Indo–European languages . accuracies are 92.7% and 94.6% for Chinese and English respectively . |
Similar Papers
Inducing Universal Semantic Tag Vectors (2020.lrec-1)
Copied to clipboard
| Challenge: | Existing semantic tags are useful for syntactically oriented downstream NLP tasks . but their size is limited and many words are out-of-vocabulary words . |
| Approach: | They propose to tagging words with semantic distinctions that are likely to be useful across semantic tasks. |
| Outcome: | The proposed semantic tagging scheme can predict unseen words with high accuracy . it distinguishes privative attributes from subsective ones, making it easier to discern fake detectives . |
Translation via Annotation: A Computational Study of Translating Classical Chinese into Japanese (2026.eacl-long)
Copied to clipboard
| Challenge: | Ancient people translated classical Chinese into Japanese using a system of annotations placed around characters. |
| Approach: | They propose to introduce an LLM-based annotation pipeline and construct a dataset from digitized open-source translation data to improve sequence tagging tasks. |
| Outcome: | The proposed method achieves high scores on direct machine translation, but could serve as a supplement to LLMs to improve the quality of character’s annotation. |
A Tour of Explicit Multilingual Semantics: Word Sense Disambiguation, Semantic Role Labeling and Semantic Parsing (2022.aacl-tutorials)
Copied to clipboard
| Challenge: | a recent advent of pretrained language models has sparked a revolution in NLP . but, there are still questions about whether current approaches capture explicit, symbolic meaning . this tutorial will review efforts to tackle three key open problems in lexical and sentence-level semantics . |
| Approach: | This tutorial reviews recent efforts to shed light on meaning in NLP . it will focus on three key open problems in lexical and sentence-level semantics . |
| Outcome: | This tutorial reviews recent efforts to shed light on meaning in NLP . it focuses on three key open problems in lexical and sentence-level semantics . |
Cross-lingual Semantic Representation for NLP with UCCA (2020.coling-tutorials)
Copied to clipboard
| Challenge: | introductory tutorial to UCCA, a symbolic meaning representation for semantic representations. |
| Approach: | This tutorial introduces UCCA, a cross-linguistically applicable framework for semantic representation . it will provide a detailed introduction to the UCca annotation guidelines, design philosophy and available resources . |
| Outcome: | The tutorial will provide a detailed introduction to the UCCA framework and compare it to other meaning representations. |
A Corpus of Adpositional Supersenses for Mandarin Chinese (2020.lrec-1)
Copied to clipboard
| 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 . |
Cross-Lingual Abstract Meaning Representation Parsing (N18-1)
Copied to clipboard
| Challenge: | Abstract Meaning Representation (AMR) research has focused on English . Qualitative analysis shows that the new parsers overcome structural differences between the languages. |
| Approach: | They propose to use an AMR parser for English and parallel corpora to learn AMR for Italian, Spanish, German and Chinese. |
| Outcome: | The proposed method overcomes structural differences between the target languages and requires no gold standard data. |
Mitigating Data Scarcity in Semantic Parsing across Languages with the Multilingual Semantic Layer and its Dataset (2024.findings-acl)
Copied to clipboard
Abelardo Carlos Martinez Lorenzo, Pere-Lluís Huguet Cabot, Karim Ghonim, Lu Xu, Hee-Soo Choi, Alberte Fernández-Castro, Roberto Navigli
| Challenge: | Large Language Models (LLMs) have advanced significantly in understanding human text, but semantic representations remain crucial for various applications. |
| Approach: | They introduce a multilingual semantic layer which decouples from disambiguation and external inventories and simplifies the task. |
| Outcome: | The proposed model reduces performance gap between languages and annotators by enabling them to understand semantic relations between concepts in any language. |
What can we learn from Semantic Tagging? (D18-1)
Copied to clipboard
| Challenge: | a recent study shows that multi-task learning improves performance of NLP tasks by exploiting similarities between tasks. |
| Approach: | They employ semantic tagging as an auxiliary task for three NLP tasks . they compare full neural network sharing, partial neural network shared and learning what to share . |
| Outcome: | The proposed model improves for part-of-speech tagging, universal dependency parsing and natural language inference. |
Building an English-Chinese Parallel Corpus Annotated with Sub-sentential Translation Techniques (2020.lrec-1)
Copied to clipboard
| Challenge: | a recent study shows that human translators often resort to different non-literal translation techniques besides literal translation . however, they receive less attention in developing natural language processing (NLP) applications. |
| Approach: | They propose to have a better semantic control of extracting paraphrases from bilingual parallel corpora. |
| Outcome: | The proposed method can automatically recognize different non-literal translation techniques . the results confirm the hypothesis of the proposed method . |
Frustratingly Simple but Surprisingly Strong: Using Language-Independent Features for Zero-shot Cross-lingual Semantic Parsing (2021.emnlp-main)
Copied to clipboard
| Challenge: | Existing training data is limited for languages other than English, so is the performance of the developed parsers. |
| Approach: | They propose to apply a pre-trained multilingual model to Italian, German and Dutch parsers where only a small number of manually annotated parses are available. |
| Outcome: | The proposed model improves on six parsers in English and Italian, German and Dutch, with the addition of universal dependency relations and universal POS tags as model-agnostic features. |