Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations
ABSApp: A Portable Weakly-Supervised Aspect-Based Sentiment Extraction System (D19-3)
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| Challenge: | a portable system for weakly-supervised aspect-based sentiment extraction is presented . ABSApp is a weakly supervised aspect based sentiment analysis system . |
| Approach: | They present a portable system for weakly-supervised aspect-based sentiment extraction . ABSApp generates domain-specific aspect and opinion lexicons based on unlabeled dataset . |
| Outcome: | The proposed system is interpretable and user friendly and can be quickly and cost-effectively used across domains . it generates domain-specific aspect and opinion lexicons, edits them, and generates an aspect-based sentiment report . the system has been successfully used in movie review analysis and convention impact analysis . |
AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models (D19-3)
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| Challenge: | Existing interpretation codebases make it difficult to apply these methods to new models and tasks. |
| Approach: | They propose a framework for interpreting NLP models that provides explanations for specific models. |
| Outcome: | The proposed framework provides interpretation primitives for any AllenNLP model and task, a suite of built-in interpretation methods, and a library of front-end visualization components. |
ALTER: Auxiliary Text Rewriting Tool for Natural Language Generation (D19-3)
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| Challenge: | Generative modeling of editing text with respect to control attributes has seen increasing progress over the past few years. |
| Approach: | They propose an auxiliary text rewriting tool that facilitates the rewrite process for natural language generation tasks. |
| Outcome: | The proposed tool facilitates the rewriting process for natural language generation tasks, such as paraphrasing, text simplification, fairness-aware text rewrite, and text style transfer. |
Applying BERT to Document Retrieval with Birch (D19-3)
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| Challenge: | Birch is an open-source document retrieval system that integrates with the Anserini information retrieval toolkit to demonstrate end-to-end search over large document collections. |
| Approach: | They propose to integrate Anserini with a BERT-based document ranking model that provides an end-to-end open-source search engine. |
| Outcome: | The proposed system outperforms existing approaches to document retrieval and question answering on standard newswire and social media test collections. |
Automatic Taxonomy Induction and Expansion (D19-3)
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Nicolas Rodolfo Fauceglia, Alfio Gliozzo, Sarthak Dash, Md. Faisal Mahbub Chowdhury, Nandana Mihindukulasooriya
| Challenge: | Knowledge Graph Induction Service (KGIS) enables automatic taxonomy induction and human-in-the-loop curation. |
| Approach: | They describe the features of the Knowledge Graph Induction Service (KGIS) KGIS allows the user to semi-automatically curate and expand the induced taxonomies through a component called Smart SpreadSheet . |
| Outcome: | The Knowledge Graph Induction Service (KGIS) is an end-to-end knowledge graph induction system. |
CFO: A Framework for Building Production NLP Systems (D19-3)
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Rishav Chakravarti, Cezar Pendus, Andrzej Sakrajda, Anthony Ferritto, Lin Pan, Michael Glass, Vittorio Castelli, J. William Murdock, Radu Florian, Salim Roukos, Avi Sil
| Challenge: | Using a new orchestration framework, we build, test, and deploy interactive NLP and IR systems to production environments. |
| Approach: | They introduce a new orchestration framework for building, experimenting with, and deploying interactive NLP and IR systems to production environments. |
| Outcome: | The proposed framework is well suited to a variety of use cases but is not suitable for academic benchmarking or industry specific use cases. |
Chameleon: A Language Model Adaptation Toolkit for Automatic Speech Recognition of Conversational Speech (D19-3)
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| Challenge: | Language model adaptation (LMA) is a promising solution for conversational speech recognition systems. |
| Approach: | They propose to use language model adaptation techniques to adapt language models to conversational speech recognition. |
| Outcome: | The proposed toolkit compares state-of-the-art language model adaptation techniques in conversational speech recognition tasks. |
Controlling Sequence-to-Sequence Models - A Demonstration on Neural-based Acrostic Generator (D19-3)
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| Challenge: | acrostic is a form of writing that the first token of each line forms a meaningful sequence. |
| Approach: | They propose a generalized acrostic generation system that can hide certain messages in a flexible pattern specified by the users. |
| Outcome: | The proposed system can hide certain messages in a flexible pattern specified by the users. |
EASSE: Easier Automatic Sentence Simplification Evaluation (D19-3)
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| Challenge: | EASSE provides access to a broad range of evaluation resources including standard automatic metrics, word-level accuracy scores and reference-independent quality estimation features. |
| Approach: | They propose to provide a Python package that provides access to automatic evaluation and comparison of Sentence Simplification (SS) systems. |
| Outcome: | The proposed tool allows comparison and understanding of the performance of Sentence Simplification (SS) systems. |
EGG: a toolkit for research on Emergence of lanGuage in Games (D19-3)
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| Challenge: | Existing approaches to simulating language emergence among deep neural agents are challenging due to the discrete nature of communication. |
| Approach: | They propose a toolkit that greatly simplifies the implementation of emergent-language communication games. |
| Outcome: | The proposed toolkit simplifies the implementation of emergent-language communication games. |
Entity resolution for noisy ASR transcripts (D19-3)
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| Challenge: | Domain-agnostic Automatic Speech Recognition systems often mistranscribe domain-specific words and phrases. |
| Approach: | They propose a method for handling ASR errors in named entities, specifically person names, for a voice-based collaboration assistant. |
| Outcome: | The proposed method improves accuracy by 40.8% on a voice-based collaboration assistant. |
EUSP: An Easy-to-Use Semantic Parsing PlatForm (D19-3)
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| Challenge: | Semantic parsing aims to map natural language utterances into structured meaning representations. |
| Approach: | They propose a modular platform that allows developers to build semantic parser from scratch. |
| Outcome: | The proposed platform achieves competitive performance on semantic parsing task and improves performance of a business search engine. |
FAMULUS: Interactive Annotation and Feedback Generation for Teaching Diagnostic Reasoning (D19-3)
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Jonas Pfeiffer, Christian M. Meyer, Claudia Schulz, Jan Kiesewetter, Jan Zottmann, Michael Sailer, Elisabeth Bauer, Frank Fischer, Martin R. Fischer, Iryna Gurevych
| Challenge: | Existing systems for technologyenhanced learning address skills on recalling, explaining, and applying knowledge, e.g., in automatically generated language learning exercises and math word problems. |
| Approach: | They propose to leverage a NLP model to support experts in their further data annotation with automatic suggestions and provide automatic feedback for students. |
| Outcome: | The proposed system improves on two user studies on diagnostic reasoning in medicine and teacher education and can be extended to further use cases. |
Gunrock: A Social Bot for Complex and Engaging Long Conversations (D19-3)
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Dian Yu, Michelle Cohn, Yi Mang Yang, Chun Yen Chen, Weiming Wen, Jiaping Zhang, Mingyang Zhou, Kevin Jesse, Austin Chau, Antara Bhowmick, Shreenath Iyer, Giritheja Sreenivasulu, Sam Davidson, Ashwin Bhandare, Zhou Yu
| Challenge: | Gunrock is a speech-based social chatbot that can be used to understand complex sentences and have in-depth conversations. |
| Approach: | They propose a system that allows users to understand complex sentences and have in-depth conversations in open domains. |
| Outcome: | The proposed system produces longer sentences, which are directly related to user engagement (e.g., ratings, number of turns). |
HARE: a Flexible Highlighting Annotator for Ranking and Exploration (D19-3)
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| Challenge: | Using NLP techniques to analyze new information domains is challenging, authors report . authors demonstrate use of HARE to rank documents based on their relevance to mobility . |
| Approach: | They propose a system for highlighting relevant information in document collections to support ranking and triage. |
| Outcome: | The proposed system can be used to rank and explore documents in clinical data . it provides tools for post-processing and qualitative analysis for model development and tuning. |
Honkling: In-Browser Personalization for Ubiquitous Keyword Spotting (D19-3)
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| Challenge: | keyword spotting systems are used for simple commands recognition on devices . however, voice-enabled web applications are few and far between . a prominent drawback is that most of these systems perform speech recognition in the cloud . |
| Approach: | Honkling is a JavaScript-based keyword spotting system that can be deployed on user devices. |
| Outcome: | Honkling is a JavaScript-based keyword spotting system that can be deployed on user devices. |
IFlyLegal: A Chinese Legal System for Consultation, Law Searching, and Document Analysis (D19-3)
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| Challenge: | Legal Tech is a system that performs legal consulting, multi-way law searching, and legal document analysis using deep contextual representations and various attention mechanisms. |
| Approach: | They propose a Chinese legal system that performs legal consulting, multi-way law searching, and legal document analysis using deep contextual representations and various attention mechanisms. |
| Outcome: | The proposed system performs legal consulting, multi-way law searching, and legal document analysis by exploiting techniques such as deep contextual representations and various attention mechanisms. |
INMT: Interactive Neural Machine Translation Prediction (D19-3)
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| Challenge: | Existing MT systems are only useful for information assimilation, and require substantial manual post processing. |
| Approach: | They propose an Interactive Machine Translation interface that assists human translators with on-the-fly hints and suggestions. |
| Outcome: | The proposed interface makes the end-to-end translation process faster, more efficient and creates high-quality translations. |
Joey NMT: A Minimalist NMT Toolkit for Novices (D19-3)
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| Challenge: | a recent study shows that novices perform better than experts in a code quiz. |
| Approach: | They present a minimalist neural machine translation toolkit based on PyTorch . they evaluate the accessibility of the toolkit in a user study . |
| Outcome: | The proposed toolkit performs comparable to more complex toolkits on standard benchmarks. |
Journalist-in-the-Loop: Continuous Learning as a Service for Rumour Analysis (D19-3)
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| Challenge: | Existing rumour analysis tools do not scale due to the large volume and velocity of user generated content. |
| Approach: | They propose to use a web-based rumour analysis tool that can continuously learn from journalists and integrate it into existing tools and platforms. |
| Outcome: | The proposed system can be easily integrated as a service into existing tools and platforms used by journalists using a REST API. |
LIDA: Lightweight Interactive Dialogue Annotator (D19-3)
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| Challenge: | Dialogue systems are dependent on the quality of the data used to train them. |
| Approach: | They propose to develop an annotation tool specifically for conversation data that handles the entire dialogue annotation pipeline from raw text to structured conversation data. |
| Outcome: | The proposed tool handles the entire dialogue annotation pipeline from raw text to structured conversation data and has a dedicated interface to resolve inter-annotator disagreements. |
LINSPECTOR WEB: A Multilingual Probing Suite for Word Representations (D19-3)
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| Challenge: | LINSPECTOR WEB is an open source multilingual inspector to analyze word embeddings. |
| Approach: | They propose to use LINSPECTOR WEB to analyze word embeddings in 28 languages. |
| Outcome: | The system performs 16 simple linguistic probing tasks for a diverse set of 28 languages. |
MAssistant: A Personal Knowledge Assistant for MOOC Learners (D19-3)
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| Challenge: | Massive Open Online Courses (MOOCs) have experienced a rapid development since 2012 . many MOOC platforms have been launched, including Coursera1 , edX2 , and Udacity3 etc. |
| Approach: | They present a personal knowledge assistant system called MAssistant for MOOC learners . MAsistants has a large-scale concept graph built from open data . it also provides a browser extension which interacts with users during video lectures . |
| Outcome: | The proposed system helps users trace the concepts they have learned in MOOCs, and to build their own concept graphs. |
MedCATTrainer: A Biomedical Free Text Annotation Interface with Active Learning and Research Use Case Specific Customisation (D19-3)
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| Challenge: | 80% of biomedical data is stored in unstructured text such as electronic health records (EHRs). |
| Approach: | They propose a web-based interface for building, improving and customising a given Named Entity Recognition and Linking (NER+L) model for biomedical domain text. |
| Outcome: | The proposed interface is designed to build, improve and customise a NER+L model for biomedical domain text and collate accurate research use case specific training data. |
Memory Grounded Conversational Reasoning (D19-3)
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| Challenge: | Existing methods to retrieve and browse memories are keyword based searches or catalog based browsing systems. |
| Approach: | They propose a conversational system which engages the user through a multi-modal, multi-turn dialog over the user’s memories. |
| Outcome: | The proposed system can perform QA over memories and make suggestions to surface related events or facts from past memories to make conversations more engaging and natural. |
Multilingual, Multi-scale and Multi-layer Visualization of Intermediate Representations (D19-3)
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| Challenge: | Currently, the main alternatives to deal with sequences are Recurrent Neural Networks (RNN) architectures and the Transformer. |
| Approach: | They propose a web-based tool that visualizes the sentence and token representations of RNNs and Transformer architectures at the sentence level. |
| Outcome: | The proposed visualization tool analyses gender inequalities in contextual word embeddings and the common language representation in a multilingual machine translation system. |
MY-AKKHARA: A Romanization-based Burmese (Myanmar) Input Method (D19-3)
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| Challenge: | MY-AKKHARA is a method used to input Burmese texts encoded in the Unicode standard, based on commonly accepted Latin transcription. |
| Approach: | They propose a method to input Burmese texts encoded in the Unicode standard based on 26 lowercase Latin letters and 26 uppercase Latin keys as shortcuts for lowercase letters. |
| Outcome: | The proposed method can input arbitrary Burmese strings with 26 lowercase Latin letters and 26 uppercase Latin characters on a QWERTY keyboard. |
NeuronBlocks: Building Your NLP DNN Models Like Playing Lego (D19-3)
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| Challenge: | Deep Neural Networks (DNN) have been widely employed in industry to address various natural language processing tasks. |
| Approach: | They propose an NLP toolkit that encapsulates neural network modules as building blocks to construct various DNN models with complex architecture. |
| Outcome: | The proposed toolkit can build, train, and test various DNN models with complex architecture. |
OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction (D19-3)
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| Challenge: | OpenNRE provides a framework to implement neural relation extraction (RE) . the toolkit provides various functional modules based on TensorFlow and PyTorch . |
| Approach: | OpenNRE is an open-source framework to implement neural relation extraction models. they also release an online system to meet real-time extraction without any training and deployment. |
| Outcome: | OpenNRE provides a framework to implement neural models for relation extraction (RE) the toolkit also includes an online system to meet real-time extraction without training and deployment . |
ParaQG: A System for Generating Questions and Answers from Paragraphs (D19-3)
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| Challenge: | Automated question generation systems generate questions from sentences and paragraphs . manual generation of questions is labour-intensive as it requires reading, parsing and understanding of long passages of text. |
| Approach: | They propose a web-based system for generating questions from sentences and paragraphs . paraQG provides an interactive interface for a user to select answers with visual insights . |
| Outcome: | The proposed system generates questions from sentences and paragraphs on a web-based platform. |
PolyResponse: A Rank-based Approach to Task-Oriented Dialogue with Application in Restaurant Search and Booking (D19-3)
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Matthew Henderson, Ivan Vulić, Iñigo Casanueva, Paweł Budzianowski, Daniela Gerz, Sam Coope, Georgios Spithourakis, Tsung-Hsien Wen, Nikola Mrkšić, Pei-Hao Su
| Challenge: | a task-oriented dialogue system is based on task-specific ontologies that constrain slots to specific values . we present a conversational search engine that can be used to search for restaurant reservations . |
| Approach: | They propose a conversational search engine that supports task-oriented dialogue . the polyresponse engine is trained on hundreds of millions of examples extracted from real conversations . |
| Outcome: | The proposed system is available in 8 different languages. |
PyOpenDial: A Python-based Domain-Independent Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules (D19-3)
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| Challenge: | a recent development of spoken dialogue systems has enabled deep learning to achieve state-of-the-art performance. |
| Approach: | They propose a Python-based domain-independent, open-source toolkit for spoken dialogue systems. |
| Outcome: | The proposed toolkit extends OpenDial's Java-based architecture and provides new functions for neural dialogue state tracking and action planning. |
Redcoat: A Collaborative Annotation Tool for Hierarchical Entity Typing (D19-3)
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| Challenge: | Recent advances in natural language processing (NLP) are fuelled by high quality annotated datasets. |
| Approach: | They introduce Redcoat, a web-based annotation tool that supports collaborative hierarchical entity typing. |
| Outcome: | The proposed annotation tool reduces the time it takes for project creators to set up and distribute projects to annotators and scales the workload depending on the number of active annotator. |
SEAGLE: A Platform for Comparative Evaluation of Semantic Encoders for Information Retrieval (D19-3)
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| Challenge: | Existing semantic text encoding models are limited in coverage and few attempts to empirically compare them on IR tasks have been made. |
| Approach: | They propose to implement word embedding aggregators and pretrained semantic encoders and to allow for their comparative evaluation on arbitrary IR collections. |
| Outcome: | The proposed model can be exploited via an easy-to-use web interface and its modular backend (micro-service architecture) can easily be extended with additional semantic search models. |
A Stylometry Toolkit for Latin Literature (D19-3)
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| Challenge: | a stylometric toolkit for analysis of Latin literary texts is available for free at www.qcrit.org/stylometry. |
| Approach: | They propose a stylometric toolkit for analysis of Latin literary texts which generates data for a diverse range of literary features and has an intuitive point-and-click interface. |
| Outcome: | The proposed toolkit generates data for a diverse range of literary features and has an intuitive point-and-click interface. |
A Summarization System for Scientific Documents (D19-3)
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Shai Erera, Michal Shmueli-Scheuer, Guy Feigenblat, Ora Peled Nakash, Odellia Boni, Haggai Roitman, Doron Cohen, Bar Weiner, Yosi Mass, Or Rivlin, Guy Lev, Achiya Jerbi, Jonathan Herzig, Yufang Hou, Charles Jochim, Martin Gleize, Francesca Bonin, Francesca Bonin, David Konopnicki
| Challenge: | a qualitative user study identified the most valuable scenarios for scientific content consumption. |
| Approach: | They propose a system that retrieves and summarizes scientific documents for a given information need. |
| Outcome: | The proposed system ingested 270,000 scientific papers and validated with human experts. |
A System for Diacritizing Four Varieties of Arabic (D19-3)
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| Challenge: | Short vowels, aka diacritics, are omitted when writing different varieties of Arabic . diacritization is essential for language learning and text-to-speech applications . |
| Approach: | They propose a system for recovering diacritics in Arabic without short vowels . they use a character-based sequence-to-sequence deep learning model . |
| Outcome: | The proposed system beats all previous SOTA systems for Arabic varieties . it uses a character-based sequence-to-sequence deep learning model . |
Tanbih: Get To Know What You Are Reading (D19-3)
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Yifan Zhang, Giovanni Da San Martino, Alberto Barrón-Cedeño, Salvatore Romeo, Jisun An, Haewoon Kwak, Todor Staykovski, Israa Jaradat, Georgi Karadzhov, Ramy Baly, Kareem Darwish, James Glass, Preslav Nakov
| Challenge: | Nowadays, more and more readers consume news online. |
| Approach: | They propose a news platform that displays news grouped into events and generates media profiles that show the general factuality of reporting, the degree of propagandistic content, hyper-partisanship, leading political ideology, general frame of reporting and stance with respect to various claims and topics of a media outlet. |
| Outcome: | The proposed news platform displays news grouped into events and generates media profiles that show the factuality of reporting, the degree of propagandistic content, hyper-partisanship, leading political ideology, general frame of reporting and stance with respect to various claims and topics of a news outlet. |
TEASPN: Framework and Protocol for Integrated Writing Assistance Environments (D19-3)
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| Challenge: | TEASPN is an open-source protocol for integrated writing assistance environments . authors propose that developers and researchers can integrate the latest developments in natural language processing with low cost. |
| Approach: | They propose a protocol and framework for integrating writing aids with writing software. |
| Outcome: | The proposed protocol standardizes the way writing software communicates with servers that implement such technologies, allowing developers and researchers to integrate the latest developments in natural language processing (NLP) with low cost. |
TellMeWhy: Learning to Explain Corrective Feedback for Second Language Learners (D19-3)
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| Challenge: | Write & Improve and Grammarly typically use canned text to explain grammatical errors, but corrective feedback with the most useful explanations may contain collocations, grammar, and contextsensitive examples. |
| Approach: | They propose to analyze sentences with corrections to identify error types and problem words and to extract grammar patterns, collocations and example sentences. |
| Outcome: | The proposed system can be used to customize explanations based on the context of the error. |
UER: An Open-Source Toolkit for Pre-training Models (D19-3)
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Zhe Zhao, Hui Chen, Jinbin Zhang, Xin Zhao, Tao Liu, Wei Lu, Xi Chen, Haotang Deng, Qi Ju, Xiaoyong Du
| Challenge: | Existing work on pre-training models have shown that it is important to use a framework to deploy various pre- training models efficiently. |
| Approach: | They propose an assemble-on-demand pre-training toolkit that assembles pre-trained models on demand and encapsulates them with rich modules. |
| Outcome: | The proposed framework can reproduce state-of-the-art models or develop models that remain unexplored. |
Visualizing Trends of Key Roles in News Articles (D19-3)
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| Challenge: | a demonstration system visualizes news trend of key roles based on natural language processing techniques . semantic role labelling and word embeddings can help users understand news topics . |
| Approach: | They propose a system that visualizes the news trend of key roles based on natural language processing techniques. |
| Outcome: | The proposed system analyzes the news trend of key roles using semantic role labelling . it also analyzes how similarities between key roles and news topics change over time . |
VizSeq: a visual analysis toolkit for text generation tasks (D19-3)
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| Challenge: | Several softwares for text evaluation are available that do not provide detailed examples. |
| Approach: | They propose a visual analysis toolkit for instance-level and corpus-level system evaluation on a wide variety of text generation tasks. |
| Outcome: | The proposed toolkit covers most common n-gram metrics and latest embedding-based metrics such as BERTScore. |
What’s Wrong with Hebrew NLP? And How to Make it Right (D19-3)
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| Challenge: | Sub-optimal performance of many morphologically rich languages (MRLs) is due to errors in early morphology disambiguation decisions, that cannot be recovered later on in the pipeline, yielding incoherent annotations on the whole. |
| Approach: | They propose to use a joint morpho-syntactic infrastructure for processing Modern Hebrew texts to provide rich and expressive annotations. |
| Outcome: | The proposed pipelines are based on a morpho-syntactic infrastructure for processing Modern Hebrew texts. |