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Deep Joint Entity Disambiguation with Local Neural Attention
AbstractWe propose a novel deep learning model for joint document-level entity disambiguation, which leverages learned neural representations. Key components are entity embeddings, a neural attention mechanism over local context windows, …...
Large-scale Opinion Relation Extraction with Distantly Supervised Neural Network
AbstractWe investigate the task of open domain opinion relation extraction. Different from works on manually labeled corpus, we propose an efficient distantly supervised framework based on pattern matching and neural …...
Lyb3b at SemEval-2018 Task 11: Machine Comprehension Task using Deep Learning Models
AbstractMachine Comprehension of text is a typical Natural Language Processing task which remains an elusive challenge. This paper is to solve the task 11 of SemEval-2018, Machine Comprehension using Commonsense …...
Figure Eight at SemEval-2019 Task 3: Ensemble of Transfer Learning Methods for Contextual Emotion Detection
AbstractThis paper describes our transfer learning-based approach to contextual emotion detection as part of SemEval-2019 Task 3. We experiment with transfer learning using pre-trained language models (ULMFiT, OpenAI GPT, and …...
Combining Thai EDUs: Principle and Implementation
Due to the lack of explicit end-of-sentence marker in Thai, Elementary Discourse Units (EDUs) are usually preferred over sentences as the basic linguistic units for processing Thai language. However, some …...
Modality Enriched Neural Network for Metaphor Detection
AbstractMetaphor as a cognitive mechanism in human’s conceptual system manifests itself an effective way for language communication. Although being intuitively sensible for human, metaphor detection is still a challenging task …...
Pheonix at SemEval-2020 Task 5: Masking the Labels Lubricates Models for Sequence Labeling
AbstractThis paper presents the deep-learning model that is submitted to the SemEval-2020 Task 5 competition: “Detecting Counterfactuals”. We participated in both Subtask1 and Subtask2. The model proposed in this paper …...
Quantifying Intimacy in Language
AbstractIntimacy is a fundamental aspect of how we relate to others in social settings. Language encodes the social information of intimacy through both topics and other more subtle cues (such …...
Retrieving Skills from Job Descriptions: A Language Model Based Extreme Multi-label Classification Framework
AbstractWe introduce a deep learning model to learn the set of enumerated job skills associated with a job description. In our analysis of a large-scale government job portal mycareersfuture.sg, we …...
What Does This Acronym Mean? Introducing a New Dataset for Acronym Identification and Disambiguation
AbstractAcronyms are the short forms of phrases that facilitate conveying lengthy sentences in documents and serve as one of the mainstays of writing. Due to their importance, identifying acronyms and …...
CS-UM6P at SemEval-2021 Task 1: A Deep Learning Model-based Pre-trained Transformer Encoder for Lexical Complexity
AbstractLexical Complexity Prediction (LCP) involves assigning a difficulty score to a particular word or expression, in a text intended for a target audience. In this paper, we introduce a new …...
Proxy Indicators for the Quality of Open-domain Dialogues
AbstractThe automatic evaluation of open-domain dialogues remains a largely unsolved challenge. Despite the abundance of work done in the field, human judges have to evaluate dialogues’ quality. As a consequence, …...
What confuses BERT? Linguistic Evaluation of Sentiment Analysis on Telecom Customer Opinion
AbstractEver-expanding evaluative texts on online forums have become an important source of sentiment analysis. This paper proposes an aspect-based annotated dataset consisting of telecom reviews on social media. We introduce …...
A Distant Supervision Corpus for Extracting Biomedical Relationships Between Chemicals, Diseases and Genes
AbstractWe introduce ChemDisGene, a new dataset for training and evaluating multi-class multi-label biomedical relation extraction models. Our dataset contains 80k biomedical research abstracts labeled with mentions of chemicals, diseases, and …...
Analyzing discourse functions with acoustic features and phone embeddings: non-lexical items in Taiwan Mandarin
AbstractNon-lexical items are expressive devices used in conversations that are not words but are nevertheless meaningful. These items play crucial roles, such as signaling turn-taking or marking stances in interactions. …...