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| {"qid":"qasper_title_Query_6","query":"Italian Event Detection Goes Deep Learning","answer_pids":["qasper_title_Passage_6"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_7","query":"Automatically Inferring Gender Associations from Language","answer_pids":["qasper_title_Passage_7"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_8","query":"A Crowd-based Evaluation of Abuse Response Strategies in Conversational Agents","answer_pids":["qasper_title_Passage_8"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_9","query":"A Dataset of German Legal Documents for Named Entity Recognition","answer_pids":["qasper_title_Passage_9"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_10","query":"Character-Level Models versus Morphology in Semantic Role Labeling","answer_pids":["qasper_title_Passage_10"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_11","query":"Look, Read and Enrich - Learning from Scientific Figures and their Captions","answer_pids":["qasper_title_Passage_11"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_12","query":"EmoAtt at EmoInt-2017: Inner attention sentence embedding for Emotion Intensity","answer_pids":["qasper_title_Passage_12"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_13","query":"Multilingual and Multi-Aspect Hate Speech Analysis","answer_pids":["qasper_title_Passage_13"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_14","query":"Semantic Web for Machine Translation: Challenges and Directions","answer_pids":["qasper_title_Passage_14"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_15","query":"Advancing Speech Recognition With No Speech Or With Noisy Speech","answer_pids":["qasper_title_Passage_15"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_16","query":"LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression","answer_pids":["qasper_title_Passage_16"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_17","query":"Neural Summarization by Extracting Sentences and Words","answer_pids":["qasper_title_Passage_17"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_18","query":"Improved Representation Learning for Predicting Commonsense Ontologies","answer_pids":["qasper_title_Passage_18"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_24","query":"Toward Interpretable Topic Discovery via Anchored Correlation Explanation","answer_pids":["qasper_title_Passage_24"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_25","query":"F-Score Driven Max Margin Neural Network for Named Entity Recognition in Chinese Social Media","answer_pids":["qasper_title_Passage_25"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_27","query":"XPersona: Evaluating Multilingual Personalized Chatbot","answer_pids":["qasper_title_Passage_27"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_29","query":"Improving Fine-grained Entity Typing with Entity Linking","answer_pids":["qasper_title_Passage_29"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_30","query":"Common-Knowledge Concept Recognition for SEVA","answer_pids":["qasper_title_Passage_30"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_31","query":"Automatic Argumentative-Zoning Using Word2vec","answer_pids":["qasper_title_Passage_31"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_32","query":"Multitask Learning for Blackmarket Tweet Detection","answer_pids":["qasper_title_Passage_32"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_33","query":"Cross-Lingual Natural Language Generation via Pre-Training","answer_pids":["qasper_title_Passage_33"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_34","query":"Hierarchical Neural Story Generation","answer_pids":["qasper_title_Passage_34"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_35","query":"Sentence Modeling via Multiple Word Embeddings and Multi-level Comparison for Semantic Textual Similarity","answer_pids":["qasper_title_Passage_35"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_36","query":"Aggressive, Repetitive, Intentional, Visible, and Imbalanced: Refining Representations for Cyberbullying Classification","answer_pids":["qasper_title_Passage_36"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_37","query":"Knowledge Amalgam: Generating Jokes and Quotes Together","answer_pids":["qasper_title_Passage_37"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_38","query":"A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization","answer_pids":["qasper_title_Passage_38"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_42","query":"Lexical Bias In Essay Level Prediction","answer_pids":["qasper_title_Passage_42"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_43","query":"LibriVoxDeEn: A Corpus for German-to-English Speech Translation and German Speech Recognition","answer_pids":["qasper_title_Passage_43"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_46","query":"THUEE system description for NIST 2019 SRE CTS Challenge","answer_pids":["qasper_title_Passage_46"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_49","query":"What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning","answer_pids":["qasper_title_Passage_49"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_50","query":"Mitigating Annotation Artifacts in Natural Language Inference Datasets to Improve Cross-dataset Generalization Ability","answer_pids":["qasper_title_Passage_50"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_102","query":"Political Speech Generation","answer_pids":["qasper_title_Passage_102"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_106","query":"Long-length Legal Document Classification","answer_pids":["qasper_title_Passage_106"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_110","query":"Sentiment Analysis On Indian Indigenous Languages: A Review On Multilingual Opinion Mining","answer_pids":["qasper_title_Passage_110"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_139","query":"Correcting Length Bias in Neural Machine Translation","answer_pids":["qasper_title_Passage_139"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_140","query":"Predicting Audience's Laughter Using Convolutional Neural Network","answer_pids":["qasper_title_Passage_140"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_141","query":"Augmenting End-to-End Dialog Systems with Commonsense Knowledge","answer_pids":["qasper_title_Passage_141"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_142","query":"HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset","answer_pids":["qasper_title_Passage_142"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_143","query":"Character n-gram Embeddings to Improve RNN Language Models","answer_pids":["qasper_title_Passage_143"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_144","query":"SWDE : A Sub-Word And Document Embedding Based Engine for Clickbait Detection","answer_pids":["qasper_title_Passage_144"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_145","query":"Reducing Gender Bias in Abusive Language Detection","answer_pids":["qasper_title_Passage_145"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_146","query":"Hungarian Layer: Logics Empowered Neural Architecture","answer_pids":["qasper_title_Passage_146"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_147","query":"Informative and Controllable Opinion Summarization","answer_pids":["qasper_title_Passage_147"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_148","query":"Using Statistical and Semantic Models for Multi-Document Summarization","answer_pids":["qasper_title_Passage_148"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_149","query":"Incremental Improvement of a Question Answering System by Re-ranking Answer Candidates using Machine Learning","answer_pids":["qasper_title_Passage_149"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_150","query":"Expeditious Generation of Knowledge Graph Embeddings","answer_pids":["qasper_title_Passage_150"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_151","query":"The Rapidly Changing Landscape of Conversational Agents","answer_pids":["qasper_title_Passage_151"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_152","query":"A Lost Croatian Cybernetic Machine Translation Program","answer_pids":["qasper_title_Passage_152"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_153","query":"Sentence Simplification with Memory-Augmented Neural Networks","answer_pids":["qasper_title_Passage_153"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_154","query":"An Interactive Machine Translation Framework for Modernizing Historical Documents","answer_pids":["qasper_title_Passage_154"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_155","query":"Clinical Information Extraction via Convolutional Neural Network","answer_pids":["qasper_title_Passage_155"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_156","query":"A Question Answering Approach to Emotion Cause Extraction","answer_pids":["qasper_title_Passage_156"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_157","query":"On the State of the Art of Evaluation in Neural Language Models","answer_pids":["qasper_title_Passage_157"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_158","query":"Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness","answer_pids":["qasper_title_Passage_158"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_159","query":"Automatic Detection of Cyberbullying in Social Media Text","answer_pids":["qasper_title_Passage_159"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_160","query":"Understanding the Radical Mind: Identifying Signals to Detect Extremist Content on Twitter","answer_pids":["qasper_title_Passage_160"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_161","query":"Hotel2vec: Learning Attribute-Aware Hotel Embeddings with Self-Supervision","answer_pids":["qasper_title_Passage_161"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_162","query":"A Fine-Grained Sentiment Dataset for Norwegian","answer_pids":["qasper_title_Passage_162"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_163","query":"Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions","answer_pids":["qasper_title_Passage_163"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_164","query":"ACUTE-EVAL: Improved Dialogue Evaluation with Optimized Questions and Multi-turn Comparisons","answer_pids":["qasper_title_Passage_164"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_165","query":"Unsupervised Domain Clusters in Pretrained Language Models","answer_pids":["qasper_title_Passage_165"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_166","query":"Different Absorption from the Same Sharing: Sifted Multi-task Learning for Fake News Detection","answer_pids":["qasper_title_Passage_166"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_167","query":"On NMT Search Errors and Model Errors: Cat Got Your Tongue?","answer_pids":["qasper_title_Passage_167"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_168","query":"Meta-Learning for Low-resource Natural Language Generation in Task-oriented Dialogue Systems","answer_pids":["qasper_title_Passage_168"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_169","query":"Unsupervised Question Answering for Fact-Checking","answer_pids":["qasper_title_Passage_169"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_170","query":"Toward Unsupervised Text Content Manipulation","answer_pids":["qasper_title_Passage_170"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_171","query":"Senti17 at SemEval-2017 Task 4: Ten Convolutional Neural Network Voters for Tweet Polarity Classification","answer_pids":["qasper_title_Passage_171"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_172","query":"ManiGAN: Text-Guided Image Manipulation","answer_pids":["qasper_title_Passage_172"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_173","query":"Dual Memory Network Model for Biased Product Review Classification","answer_pids":["qasper_title_Passage_173"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_174","query":"Alternative Weighting Schemes for ELMo Embeddings","answer_pids":["qasper_title_Passage_174"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_175","query":"Generating Clues for Gender based Occupation De-biasing in Text","answer_pids":["qasper_title_Passage_175"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_176","query":"Prototype-to-Style: Dialogue Generation with Style-Aware Editing on Retrieval Memory","answer_pids":["qasper_title_Passage_176"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_177","query":"Relative contributions of Shakespeare and Fletcher in Henry VIII: An Analysis Based on Most Frequent Words and Most Frequent Rhythmic Patterns","answer_pids":["qasper_title_Passage_177"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_178","query":"A Short Review of Ethical Challenges in Clinical Natural Language Processing","answer_pids":["qasper_title_Passage_178"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_179","query":"Outline Generation: Understanding the Inherent Content Structure of Documents","answer_pids":["qasper_title_Passage_179"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_180","query":"Affect-LM: A Neural Language Model for Customizable Affective Text Generation","answer_pids":["qasper_title_Passage_180"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_181","query":"Experiments in Detecting Persuasion Techniques in the News","answer_pids":["qasper_title_Passage_181"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_182","query":"Duluth at SemEval-2017 Task 6: Language Models in Humor Detection","answer_pids":["qasper_title_Passage_182"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_183","query":"Towards Understanding Gender Bias in Relation Extraction","answer_pids":["qasper_title_Passage_183"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_184","query":"A Richly Annotated Corpus for Different Tasks in Automated Fact-Checking","answer_pids":["qasper_title_Passage_184"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_185","query":"Efficient Transfer Learning Schemes for Personalized Language Modeling using Recurrent Neural Network","answer_pids":["qasper_title_Passage_185"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_186","query":"EiTAKA at SemEval-2018 Task 1: An Ensemble of N-Channels ConvNet and XGboost Regressors for Emotion Analysis of Tweets","answer_pids":["qasper_title_Passage_186"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_187","query":"Categorization in the Wild: Generalizing Cognitive Models to Naturalistic Data across Languages","answer_pids":["qasper_title_Passage_187"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_188","query":"Subword ELMo","answer_pids":["qasper_title_Passage_188"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_189","query":"Detecting Offensive Language in Tweets Using Deep Learning","answer_pids":["qasper_title_Passage_189"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_190","query":"Towards Better Understanding of Spontaneous Conversations: Overcoming Automatic Speech Recognition Errors With Intent Recognition","answer_pids":["qasper_title_Passage_190"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_191","query":"Morfessor EM+Prune: Improved Subword Segmentation with Expectation Maximization and Pruning","answer_pids":["qasper_title_Passage_191"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_192","query":"Polylingual Wordnet","answer_pids":["qasper_title_Passage_192"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_193","query":"Interview: A Large-Scale Open-Source Corpus of Media Dialog","answer_pids":["qasper_title_Passage_193"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_194","query":"MetaLDA: a Topic Model that Efficiently Incorporates Meta information","answer_pids":["qasper_title_Passage_194"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_195","query":"Twitter Job\/Employment Corpus: A Dataset of Job-Related Discourse Built with Humans in the Loop","answer_pids":["qasper_title_Passage_195"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_196","query":"PAMPO: using pattern matching and pos-tagging for effective Named Entities recognition in Portuguese","answer_pids":["qasper_title_Passage_196"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_197","query":"Predicting the Role of Political Trolls in Social Media","answer_pids":["qasper_title_Passage_197"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_198","query":"Text Understanding with the Attention Sum Reader Network","answer_pids":["qasper_title_Passage_198"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_199","query":"Modeling German Verb Argument Structures: LSTMs vs. Humans","answer_pids":["qasper_title_Passage_199"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_200","query":"Mapping Languages and Demographics with Georeferenced Corpora","answer_pids":["qasper_title_Passage_200"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_201","query":"Fine-tune BERT for Extractive Summarization","answer_pids":["qasper_title_Passage_201"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_202","query":"Content-Based Table Retrieval for Web Queries","answer_pids":["qasper_title_Passage_202"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_203","query":"Query-bag Matching with Mutual Coverage for Information-seeking Conversations in E-commerce","answer_pids":["qasper_title_Passage_203"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_204","query":"A survey of cross-lingual features for zero-shot cross-lingual semantic parsing","answer_pids":["qasper_title_Passage_204"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_205","query":"Building a robust sentiment lexicon with (almost) no resource","answer_pids":["qasper_title_Passage_205"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_206","query":"SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization","answer_pids":["qasper_title_Passage_206"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_207","query":"Generating Black-Box Adversarial Examples for Text Classifiers Using a Deep Reinforced Model","answer_pids":["qasper_title_Passage_207"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_208","query":"How multilingual is Multilingual BERT?","answer_pids":["qasper_title_Passage_208"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_209","query":"And the Winner is ...: Bayesian Twitter-based Prediction on 2016 U.S. Presidential Election","answer_pids":["qasper_title_Passage_209"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_210","query":"Iterative Multi-document Neural Attention for Multiple Answer Prediction","answer_pids":["qasper_title_Passage_210"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_211","query":"What to do about non-standard (or non-canonical) language in NLP","answer_pids":["qasper_title_Passage_211"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_212","query":"Tweet2Vec: Learning Tweet Embeddings Using Character-level CNN-LSTM Encoder-Decoder","answer_pids":["qasper_title_Passage_212"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_213","query":"Learning Scripts as Hidden Markov Models","answer_pids":["qasper_title_Passage_213"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_214","query":"Deep Learning for Hate Speech Detection in Tweets","answer_pids":["qasper_title_Passage_214"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_215","query":"The Social Dynamics of Language Change in Online Networks","answer_pids":["qasper_title_Passage_215"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_216","query":"Unsupervised Terminological Ontology Learning based on Hierarchical Topic Modeling","answer_pids":["qasper_title_Passage_216"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_217","query":"Recommendation Chart of Domains for Cross-Domain Sentiment Analysis:Findings of A 20 Domain Study","answer_pids":["qasper_title_Passage_217"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_218","query":"NRC-Canada at SMM4H Shared Task: Classifying Tweets Mentioning Adverse Drug Reactions and Medication Intake","answer_pids":["qasper_title_Passage_218"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_219","query":"Transforming Wikipedia into Augmented Data for Query-Focused Summarization","answer_pids":["qasper_title_Passage_219"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_220","query":"Read, Highlight and Summarize: A Hierarchical Neural Semantic Encoder-based Approach","answer_pids":["qasper_title_Passage_220"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_221","query":"Reinforced Multi-task Approach for Multi-hop Question Generation","answer_pids":["qasper_title_Passage_221"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_222","query":"Sequence Labeling Parsing by Learning Across Representations","answer_pids":["qasper_title_Passage_222"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_223","query":"Optimizing Differentiable Relaxations of Coreference Evaluation Metrics","answer_pids":["qasper_title_Passage_223"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_224","query":"Transfer Learning for Low-Resource Neural Machine Translation","answer_pids":["qasper_title_Passage_224"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_225","query":"Leveraging Frequent Query Substructures to Generate Formal Queries for Complex Question Answering","answer_pids":["qasper_title_Passage_225"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_226","query":"SubGram: Extending Skip-gram Word Representation with Substrings","answer_pids":["qasper_title_Passage_226"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_227","query":"Plain English Summarization of Contracts","answer_pids":["qasper_title_Passage_227"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_228","query":"Bayesian Models for Unit Discovery on a Very Low Resource Language","answer_pids":["qasper_title_Passage_228"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_229","query":"It's All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Substitution","answer_pids":["qasper_title_Passage_229"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_230","query":"Semantic Mask for Transformer based End-to-End Speech Recognition","answer_pids":["qasper_title_Passage_230"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_231","query":"Sentiment Analysis of Czech Texts: An Algorithmic Survey","answer_pids":["qasper_title_Passage_231"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_232","query":"Phrase Table as Recommendation Memory for Neural Machine Translation","answer_pids":["qasper_title_Passage_232"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_233","query":"Semantic Product Search","answer_pids":["qasper_title_Passage_233"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_234","query":"Unsupervised Identification of Study Descriptors in Toxicology Research: An Experimental Study","answer_pids":["qasper_title_Passage_234"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_235","query":"Applying Cyclical Learning Rate to Neural Machine Translation","answer_pids":["qasper_title_Passage_235"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_236","query":"Clotho: An Audio Captioning Dataset","answer_pids":["qasper_title_Passage_236"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_237","query":"Evaluating Multimodal Representations on Sentence Similarity: vSTS, Visual Semantic Textual Similarity Dataset","answer_pids":["qasper_title_Passage_237"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_238","query":"Application of Pre-training Models in Named Entity Recognition","answer_pids":["qasper_title_Passage_238"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_239","query":"Utilizing BERT Intermediate Layers for Aspect Based Sentiment Analysis and Natural Language Inference","answer_pids":["qasper_title_Passage_239"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_240","query":"Semantic Enrichment of Nigerian Pidgin English for Contextual Sentiment Classification","answer_pids":["qasper_title_Passage_240"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_241","query":"GWU NLP Lab at SemEval-2019 Task 3: EmoContext: Effective Contextual Information in Models for Emotion Detection in Sentence-level in a Multigenre Corpus","answer_pids":["qasper_title_Passage_241"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_242","query":"Unfolding and Shrinking Neural Machine Translation Ensembles","answer_pids":["qasper_title_Passage_242"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_243","query":"Location, Occupation, and Semantics based Socioeconomic Status Inference on Twitter","answer_pids":["qasper_title_Passage_243"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_244","query":"Acquiring Annotated Data with Cross-lingual Explicitation for Implicit Discourse Relation Classification","answer_pids":["qasper_title_Passage_244"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_245","query":"Information Extraction with Character-level Neural Networks and Free Noisy Supervision","answer_pids":["qasper_title_Passage_245"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_246","query":"Socioeconomic Dependencies of Linguistic Patterns in Twitter: A Multivariate Analysis","answer_pids":["qasper_title_Passage_246"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_247","query":"HoME: a Household Multimodal Environment","answer_pids":["qasper_title_Passage_247"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_248","query":"Extrapolation in NLP","answer_pids":["qasper_title_Passage_248"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_249","query":"Learning variable length units for SMT between related languages via Byte Pair Encoding","answer_pids":["qasper_title_Passage_249"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_250","query":"Identifying Nuances in Fake News vs. Satire: Using Semantic and Linguistic Cues","answer_pids":["qasper_title_Passage_250"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_251","query":"Recurrent Neural Network Grammars","answer_pids":["qasper_title_Passage_251"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_252","query":"BERT-Based Multi-Head Selection for Joint Entity-Relation Extraction","answer_pids":["qasper_title_Passage_252"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_253","query":"Assessing Gender Bias in Machine Translation -- A Case Study with Google Translate","answer_pids":["qasper_title_Passage_253"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_254","query":"Multi-task Learning for Low-resource Second Language Acquisition Modeling","answer_pids":["qasper_title_Passage_254"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_255","query":"WorldTree: A Corpus of Explanation Graphs for Elementary Science Questions supporting Multi-Hop Inference","answer_pids":["qasper_title_Passage_255"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_256","query":"Neural network approach to classifying alarming student responses to online assessment","answer_pids":["qasper_title_Passage_256"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_257","query":"Multimodal Attribute Extraction","answer_pids":["qasper_title_Passage_257"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_259","query":"Morphology-based Entity and Relational Entity Extraction Framework for Arabic","answer_pids":["qasper_title_Passage_259"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_260","query":"Building a Massive Corpus for Named Entity Recognition Using Free Open Data Sources","answer_pids":["qasper_title_Passage_260"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_262","query":"Contextual Encoding for Translation Quality Estimation","answer_pids":["qasper_title_Passage_262"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_263","query":"Named Entity Recognition in Twitter using Images and Text","answer_pids":["qasper_title_Passage_263"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_264","query":"A Transformer-based approach to Irony and Sarcasm detection","answer_pids":["qasper_title_Passage_264"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_265","query":"r\/Fakeddit: A New Multimodal Benchmark Dataset for Fine-grained Fake News Detection","answer_pids":["qasper_title_Passage_265"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_266","query":"Improved Abusive Comment Moderation with User Embeddings","answer_pids":["qasper_title_Passage_266"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_267","query":"Bridging the Gap: Incorporating a Semantic Similarity Measure for Effectively Mapping PubMed Queries to Documents","answer_pids":["qasper_title_Passage_267"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_268","query":"Amobee at SemEval-2017 Task 4: Deep Learning System for Sentiment Detection on Twitter","answer_pids":["qasper_title_Passage_268"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_277","query":"Sentiment Analysis of Code-Mixed Indian Languages: An Overview of SAIL_Code-Mixed Shared Task @ICON-2017","answer_pids":["qasper_title_Passage_277"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_278","query":"A Holistic Natural Language Generation Framework for the Semantic Web","answer_pids":["qasper_title_Passage_278"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_280","query":"And That's A Fact: Distinguishing Factual and Emotional Argumentation in Online Dialogue","answer_pids":["qasper_title_Passage_280"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_281","query":"A Focus on Neural Machine Translation for African Languages","answer_pids":["qasper_title_Passage_281"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_282","query":"Generating Texts with Integer Linear Programming","answer_pids":["qasper_title_Passage_282"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_283","query":"Learning from Dialogue after Deployment: Feed Yourself, Chatbot!","answer_pids":["qasper_title_Passage_283"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_284","query":"Meta Multi-Task Learning for Sequence Modeling","answer_pids":["qasper_title_Passage_284"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_285","query":"Prediction Uncertainty Estimation for Hate Speech Classification","answer_pids":["qasper_title_Passage_285"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_286","query":"A Generalized Recurrent Neural Architecture for Text Classification with Multi-Task Learning","answer_pids":["qasper_title_Passage_286"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_288","query":"Spoken Conversational Search for General Knowledge","answer_pids":["qasper_title_Passage_288"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_291","query":"Tackling Online Abuse: A Survey of Automated Abuse Detection Methods","answer_pids":["qasper_title_Passage_291"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_292","query":"Lancaster A at SemEval-2017 Task 5: Evaluation metrics matter: predicting sentiment from financial news headlines","answer_pids":["qasper_title_Passage_292"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_293","query":"Reducing Gender Bias in Neural Machine Translation as a Domain Adaptation Problem","answer_pids":["qasper_title_Passage_293"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_294","query":"Learning Distributed Representations of Sentences from Unlabelled Data","answer_pids":["qasper_title_Passage_294"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_295","query":"Shallow Discourse Parsing with Maximum Entropy Model","answer_pids":["qasper_title_Passage_295"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_296","query":"Exploring Domain Shift in Extractive Text Summarization","answer_pids":["qasper_title_Passage_296"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_297","query":"Multilingual is not enough: BERT for Finnish","answer_pids":["qasper_title_Passage_297"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_298","query":"A Surrogate-based Generic Classifier for Chinese TV Series Reviews","answer_pids":["qasper_title_Passage_298"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_299","query":"A Causality-Guided Prediction of the TED Talk Ratings from the Speech-Transcripts using Neural Networks","answer_pids":["qasper_title_Passage_299"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_300","query":"Emotional Neural Language Generation Grounded in Situational Contexts","answer_pids":["qasper_title_Passage_300"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_301","query":"Verb Pattern: A Probabilistic Semantic Representation on Verbs","answer_pids":["qasper_title_Passage_301"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_302","query":"Enhanced Twitter Sentiment Classification Using Contextual Information","answer_pids":["qasper_title_Passage_302"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_303","query":"Efficient Calculation of Bigram Frequencies in a Corpus of Short Texts","answer_pids":["qasper_title_Passage_303"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_304","query":"autoNLP: NLP Feature Recommendations for Text Analytics Applications","answer_pids":["qasper_title_Passage_304"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_305","query":"A Simple Joint Model for Improved Contextual Neural Lemmatization","answer_pids":["qasper_title_Passage_305"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_306","query":"Pathological speech detection using x-vector embeddings","answer_pids":["qasper_title_Passage_306"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_307","query":"Universal Dependencies for Learner English","answer_pids":["qasper_title_Passage_307"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_308","query":"Rethinking Attribute Representation and Injection for Sentiment Classification","answer_pids":["qasper_title_Passage_308"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_309","query":"Improving Zero-shot Translation with Language-Independent Constraints","answer_pids":["qasper_title_Passage_309"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_310","query":"Neural Machine Translation for Low Resource Languages using Bilingual Lexicon Induced from Comparable Corpora","answer_pids":["qasper_title_Passage_310"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_311","query":"Nematus: a Toolkit for Neural Machine Translation","answer_pids":["qasper_title_Passage_311"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_312","query":"One Model to Learn Both: Zero Pronoun Prediction and Translation","answer_pids":["qasper_title_Passage_312"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_313","query":"Translating Questions into Answers using DBPedia n-triples","answer_pids":["qasper_title_Passage_313"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_314","query":"UIT-ViIC: A Dataset for the First Evaluation on Vietnamese Image Captioning","answer_pids":["qasper_title_Passage_314"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_315","query":"Dual Co-Matching Network for Multi-choice Reading Comprehension","answer_pids":["qasper_title_Passage_315"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_316","query":"Who's to say what's funny? A computer using Language Models and Deep Learning, That's Who!","answer_pids":["qasper_title_Passage_316"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_317","query":"Sequential Neural Networks as Automata","answer_pids":["qasper_title_Passage_317"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_318","query":"Memory-Augmented Recurrent Networks for Dialogue Coherence","answer_pids":["qasper_title_Passage_318"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_319","query":"\"Wait, I'm Still Talking!\"Predicting the Dialogue Interaction Behavior Using Imagine-Then-Arbitrate Model","answer_pids":["qasper_title_Passage_319"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_320","query":"Creating a Real-Time, Reproducible Event Dataset","answer_pids":["qasper_title_Passage_320"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_321","query":"On the Computational Power of RNNs","answer_pids":["qasper_title_Passage_321"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_322","query":"TwistBytes -- Hierarchical Classification at GermEval 2019: walking the fine line (of recall and precision)","answer_pids":["qasper_title_Passage_322"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_323","query":"An Investigation into the Effectiveness of Enhancement in ASR Training and Test for Chime-5 Dinner Party Transcription","answer_pids":["qasper_title_Passage_323"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_324","query":"A Corpus for Multilingual Document Classification in Eight Languages","answer_pids":["qasper_title_Passage_324"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_325","query":"\"i have a feeling trump will win..................\": Forecasting Winners and Losers from User Predictions on Twitter","answer_pids":["qasper_title_Passage_325"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_326","query":"Topic-Specific Sentiment Analysis Can Help Identify Political Ideology","answer_pids":["qasper_title_Passage_326"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_327","query":"AC-BLSTM: Asymmetric Convolutional Bidirectional LSTM Networks for Text Classification","answer_pids":["qasper_title_Passage_327"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_329","query":"Selecting Artificially-Generated Sentences for Fine-Tuning Neural Machine Translation","answer_pids":["qasper_title_Passage_329"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_330","query":"Linguistic Input Features Improve Neural Machine Translation","answer_pids":["qasper_title_Passage_330"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_331","query":"What can we learn from Semantic Tagging?","answer_pids":["qasper_title_Passage_331"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_332","query":"Learning to Select Bi-Aspect Information for Document-Scale Text Content Manipulation","answer_pids":["qasper_title_Passage_332"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_333","query":"The Power of Communities: A Text Classification Model with Automated Labeling Process Using Network Community Detection","answer_pids":["qasper_title_Passage_333"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_334","query":"On the Unintended Social Bias of Training Language Generation Models with Data from Local Media","answer_pids":["qasper_title_Passage_334"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_335","query":"CAp 2017 challenge: Twitter Named Entity Recognition","answer_pids":["qasper_title_Passage_335"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_336","query":"Forget Me Not: Reducing Catastrophic Forgetting for Domain Adaptation in Reading Comprehension","answer_pids":["qasper_title_Passage_336"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_337","query":"Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation","answer_pids":["qasper_title_Passage_337"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_338","query":"Adversarial Training for Aspect-Based Sentiment Analysis with BERT","answer_pids":["qasper_title_Passage_338"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_339","query":"Two are Better than One: An Ensemble of Retrieval- and Generation-Based Dialog Systems","answer_pids":["qasper_title_Passage_339"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_341","query":"Improving Yor\\`ub\\'a Diacritic Restoration","answer_pids":["qasper_title_Passage_341"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_342","query":"Fixed-Size Ordinally Forgetting Encoding Based Word Sense Disambiguation","answer_pids":["qasper_title_Passage_342"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_343","query":"Gated Recurrent Neural Tensor Network","answer_pids":["qasper_title_Passage_343"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_344","query":"360{\\deg} Stance Detection","answer_pids":["qasper_title_Passage_344"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_345","query":"Similarity measure for Public Persons","answer_pids":["qasper_title_Passage_345"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_348","query":"Neuro-symbolic Architectures for Context Understanding","answer_pids":["qasper_title_Passage_348"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_361","query":"Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasets","answer_pids":["qasper_title_Passage_361"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_371","query":"Controllable Sentence Simplification","answer_pids":["qasper_title_Passage_371"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_374","query":"Patient Knowledge Distillation for BERT Model Compression","answer_pids":["qasper_title_Passage_374"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_385","query":"Auditing ImageNet: Towards a Model-driven Framework for Annotating Demographic Attributes of Large-Scale Image Datasets","answer_pids":["qasper_title_Passage_385"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_386","query":"Enhanced Neural Machine Translation by Learning from Draft","answer_pids":["qasper_title_Passage_386"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_395","query":"Real-World Conversational AI for Hotel Bookings","answer_pids":["qasper_title_Passage_395"],"dataset":"qasper_title"} | |
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| {"qid":"qasper_title_Query_408","query":"Incorporating Word and Subword Units in Unsupervised Machine Translation Using Language Model Rescoring","answer_pids":["qasper_title_Passage_408"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_409","query":"QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions","answer_pids":["qasper_title_Passage_409"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_410","query":"The Medical Scribe: Corpus Development and Model Performance Analyses","answer_pids":["qasper_title_Passage_410"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_411","query":"Iterative Policy Learning in End-to-End Trainable Task-Oriented Neural Dialog Models","answer_pids":["qasper_title_Passage_411"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_412","query":"Personalized Taste and Cuisine Preference Modeling via Images","answer_pids":["qasper_title_Passage_412"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_413","query":"Regressing Word and Sentence Embeddings for Regularization of Neural Machine Translation","answer_pids":["qasper_title_Passage_413"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_414","query":"Automatic Extraction of Personality from Text: Challenges and Opportunities","answer_pids":["qasper_title_Passage_414"],"dataset":"qasper_title"} | |
| {"qid":"qasper_title_Query_415","query":"How to evaluate sentiment classifiers for Twitter time-ordered data?","answer_pids":["qasper_title_Passage_415"],"dataset":"qasper_title"} | |