{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/cg/papers/16","list_of":"/task/cg","task":"NER","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":16,"pages_in_order":18,"rows_per_page":100,"rows":[1501,1600],"of":1729,"counts":{"archive_papers_tagged":1729,"with_a_code_link":665,"where_syntology_ran_a_sample":70,"not_listed_spam_title":0,"listed":1729,"listed_where_code_ran":70,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":61,"every_run_a_failure_of_syntologys_instrument":9,"listed_with_a_run_with_no_instrument_failure":61,"listed_every_run_a_failure_of_syntologys_instrument":9,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/cg","prev":"/task/cg/papers/15","next":"/task/cg/papers/17","papers":[{"url":null,"slug":"development-and-evaluation-of-three-named","title":"Development and Evaluation of Three Named Entity Recognition Systems for Serbian - The Case of Personal Names","date":"2019-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-ner-models-by-exploiting-named","title":"Improving NER Models by exploiting Named Entity Gazetteer as External Knowledge","date":"2019-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"morphobert-a-persian-ner-system-with-bert-and","title":"MorphoBERT: a Persian NER System with BERT and Morphological Analysis","date":"2019-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multilingual-language-models-for-named-entity","title":"Multilingual Language Models for Named Entity Recognition in German and English","date":"2019-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"projecting-named-entity-recognizers-without","title":"Projecting named entity recognizers without annotated or parallel corpora","date":"2019-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-learning-with-contextual","title":"Adversarial Learning with Contextual Embeddings for Zero-resource Cross-lingual Classification and NER","date":"2019-08-31","arxiv_id":"1909.00153","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-morpho-syntactically-informed-lstm-crf","title":"A Morpho-Syntactically Informed LSTM-CRF Model for Named Entity Recognition","date":"2019-08-27","arxiv_id":"1908.10261","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-neural-sequence-labeling-with","title":"Position-Aware Self-Attention based Neural Sequence Labeling","date":"2019-08-24","arxiv_id":"1908.09128","repositories_listed":0,"syntology":null},{"url":null,"slug":"query-based-named-entity-recognition","title":"Query-Based Named Entity Recognition","date":"2019-08-24","arxiv_id":"1908.09138","repositories_listed":0,"syntology":null},{"url":null,"slug":"flexner-a-flexible-lstm-cnn-stack-framework","title":"FlexNER: A Flexible LSTM-CNN Stack Framework for Named Entity Recognition","date":"2019-08-14","arxiv_id":"1908.05009","repositories_listed":0,"syntology":null},{"url":null,"slug":"building-a-massive-corpus-for-named-entity","title":"Building a Massive Corpus for Named Entity Recognition using Free Open Data Sources","date":"2019-08-13","arxiv_id":"1908.05758","repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-information-extraction-patterns","title":"Generating Information Extraction Patterns from Overlapping and Variable Length Annotations using Sequence Alignment","date":"2019-08-09","arxiv_id":"1908.03594","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-and-accurate-capitalization-and","title":"Fast and Accurate Capitalization and Punctuation for Automatic Speech Recognition Using Transformer and Chunk Merging","date":"2019-08-07","arxiv_id":"1908.02404","repositories_listed":0,"syntology":null},{"url":null,"slug":"augmenting-named-entity-recognition-with","title":"Augmenting Named Entity Recognition with Commonsense Knowledge","date":"2019-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"bsnlp2019-shared-task-submission-multisource","title":"BSNLP2019 Shared Task Submission: Multisource Neural NER Transfer","date":"2019-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-swedish-poligraph-a-semantic-graph-for","title":"The Swedish PoliGraph: A Semantic Graph for Argument Mining of Swedish Parliamentary Data","date":"2019-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-lingual-transfer-for-distantly","title":"Cross-Lingual Transfer for Distantly Supervised and Low-resources Indonesian NER","date":"2019-07-25","arxiv_id":"1907.11158","repositories_listed":0,"syntology":null},{"url":"/paper/joint-learning-of-named-entity-recognition","slug":"joint-learning-of-named-entity-recognition","title":"Joint Learning of Named Entity Recognition and Entity Linking","date":"2019-07-18","arxiv_id":"1907.08243","repositories_listed":0,"syntology":null},{"url":null,"slug":"medcattrainer-a-biomedical-free-text","title":"MedCATTrainer: A Biomedical Free Text Annotation Interface with Active Learning and Research Use Case Specific Customisation","date":"2019-07-16","arxiv_id":"1907.07322","repositories_listed":0,"syntology":null},{"url":null,"slug":"ranking-sentences-from-product-description","title":"Ranking sentences from product description & bullets for better search","date":"2019-07-15","arxiv_id":"1907.06330","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-semi-markov-structured-support-vector","title":"A Semi-Markov Structured Support Vector Machine Model for High-Precision Named Entity Recognition","date":"2019-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptation-d-une-m-etagrammaire-du-fran-ccais","title":"Adaptation d'une m\\'etagrammaire du fran\\ccais contemporain au fran\\ccais m\\'edi\\'eval (Adapting an existing metagrammar for Contemporary French to Medieval French)","date":"2019-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"alpacatag-an-active-learning-based-crowd","title":"AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging","date":"2019-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"corpus-creation-and-analysis-for-named-entity","title":"Corpus Creation and Analysis for Named Entity Recognition in Telugu-English Code-Mixed Social Media Data","date":"2019-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dual-adversarial-neural-transfer-for-low","title":"Dual Adversarial Neural Transfer for Low-Resource Named Entity Recognition","date":"2019-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"named-entity-recognition-on-code-switched-2","title":"Named Entity Recognition on Code-Switched Data: Overview of the CALCS 2018 Shared Task","date":"2019-06-10","arxiv_id":"1906.04138","repositories_listed":0,"syntology":null},{"url":null,"slug":"back-attention-knowledge-transfer-for-low","title":"Converse Attention Knowledge Transfer for Low-Resource Named Entity Recognition","date":"2019-06-04","arxiv_id":"1906.01183","repositories_listed":0,"syntology":null},{"url":"/paper/nne-a-dataset-for-nested-named-entity","slug":"nne-a-dataset-for-nested-named-entity","title":"NNE: A Dataset for Nested Named Entity Recognition in English Newswire","date":"2019-06-04","arxiv_id":"1906.01359","repositories_listed":0,"syntology":null},{"url":null,"slug":"190600282","title":"Biomedical Named Entity Recognition via Reference-Set Augmented Bootstrapping","date":"2019-06-01","arxiv_id":"1906.00282","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-de-identification-a-new-entity-1","title":"Audio De-identification - a New Entity Recognition Task","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"better-modeling-of-incomplete-annotations-for","title":"Better Modeling of Incomplete Annotations for Named Entity Recognition","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"pooled-contextualized-embeddings-for-named","title":"Pooled Contextualized Embeddings for Named Entity Recognition","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unh-at-semeval-2019-task-12-toponym","title":"UNH at SemEval-2019 Task 12: Toponym Resolution in Scientific Papers","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unimelb-at-semeval-2019-task-12-multi-model","title":"UniMelb at SemEval-2019 Task 12: Multi-model combination for toponym resolution","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"university-of-arizona-at-semeval-2019-task-12","title":"University of Arizona at SemEval-2019 Task 12: Deep-Affix Named Entity Recognition of Geolocation Entities","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-task-learning-framework-for-1","title":"A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels","date":"2019-05-17","arxiv_id":"1905.07464","repositories_listed":0,"syntology":null},{"url":"/paper/neural-metric-learning-for-fast-end-to-end","slug":"neural-metric-learning-for-fast-end-to-end","title":"Neural Metric Learning for Fast End-to-End Relation Extraction","date":"2019-05-17","arxiv_id":"1905.07458","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-co-guided-neural-network-for-person-name","title":"A Co-guided Neural Network for Person Name Recognition in Academic Homepages","date":"2019-05-14","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-for-scientific-data-chain","title":"Transfer Learning for Scientific Data Chain Extraction in Small Chemical Corpus with BERT-CRF Model","date":"2019-05-13","arxiv_id":"1905.05615","repositories_listed":0,"syntology":null},{"url":null,"slug":"models-in-the-wild-on-corruption-robustness","title":"Models in the Wild: On Corruption Robustness of NLP Systems","date":"2019-05-05","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"datnet-dual-adversarial-transfer-for-low","title":"DATNet: Dual Adversarial Transfer for Low-resource Named Entity Recognition","date":"2019-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"terminologies-augmented-recurrent-neural","title":"Terminologies augmented recurrent neural network model for clinical named entity recognition","date":"2019-04-25","arxiv_id":"1904.11473","repositories_listed":0,"syntology":null},{"url":null,"slug":"personalized-sentence-generation-using","title":"Personalized sentence generation using generative adversarial networks with author-specific word usage","date":"2019-04-20","arxiv_id":"1904.09442","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-task-learning-approach-for-named","title":"A Multi-task Learning Approach for Named Entity Recognition using Local Detection","date":"2019-04-05","arxiv_id":"1904.03300","repositories_listed":0,"syntology":null},{"url":null,"slug":"effective-context-and-fragment-feature-usage","title":"Effective Context and Fragment Feature Usage for Named Entity Recognition","date":"2019-04-05","arxiv_id":"1904.03305","repositories_listed":0,"syntology":null},{"url":null,"slug":"handling-noisy-labels-for-robustly-learning","title":"Handling Noisy Labels for Robustly Learning from Self-Training Data for Low-Resource Sequence Labeling","date":"2019-03-28","arxiv_id":"1903.12008","repositories_listed":0,"syntology":null},{"url":null,"slug":"in-search-of-meaning-lessons-resources-and","title":"In Search of Meaning: Lessons, Resources and Next Steps for Computational Analysis of Financial Discourse","date":"2019-03-28","arxiv_id":"1903.12271","repositories_listed":0,"syntology":null},{"url":null,"slug":"ner-and-pos-when-nothing-is-capitalized","title":"ner and pos when nothing is capitalized","date":"2019-03-27","arxiv_id":"1903.11222","repositories_listed":0,"syntology":null},{"url":"/paper/cloze-driven-pretraining-of-self-attention","slug":"cloze-driven-pretraining-of-self-attention","title":"Cloze-driven Pretraining of Self-attention Networks","date":"2019-03-19","arxiv_id":"1903.07785","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-de-identification-a-new-entity","title":"Audio De-identification: A New Entity Recognition Task","date":"2019-03-17","arxiv_id":"1903.07037","repositories_listed":0,"syntology":null},{"url":null,"slug":"overview-of-the-ugglan-entity-discovery-and","title":"Overview of the Ugglan Entity Discovery and Linking System","date":"2019-03-13","arxiv_id":"1903.05498","repositories_listed":0,"syntology":null},{"url":null,"slug":"syllable-based-neural-named-entity","title":"Syllable-based Neural Named Entity Recognition for Myanmar Language","date":"2019-03-12","arxiv_id":"1903.04739","repositories_listed":0,"syntology":null},{"url":null,"slug":"named-entity-recognition-for-electronic","title":"Named Entity Recognition for Electronic Health Records: A Comparison of Rule-based and Machine Learning Approaches","date":"2019-03-10","arxiv_id":"1903.03985","repositories_listed":0,"syntology":null},{"url":null,"slug":"f10-sgd-fast-training-of-elastic-net-linear","title":"F10-SGD: Fast Training of Elastic-net Linear Models for Text Classification and Named-entity Recognition","date":"2019-02-27","arxiv_id":"1902.10649","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-task-learning-with-contextualized-word","title":"Multi-Task Learning with Contextualized Word Representations for Extented Named Entity Recognition","date":"2019-02-26","arxiv_id":"1902.10118","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-for-sequences-via-learning","title":"Transfer Learning for Sequences via Learning to Collocate","date":"2019-02-25","arxiv_id":"1902.09092","repositories_listed":0,"syntology":null},{"url":null,"slug":"pretrained-language-model-transfer-on-neural","title":"Pretrained language model transfer on neural named entity recognition in Indonesian conversational texts","date":"2019-02-21","arxiv_id":"1902.07938","repositories_listed":0,"syntology":null},{"url":null,"slug":"revised-jnlpba-corpus-a-revised-version-of","title":"Revised JNLPBA Corpus: A Revised Version of Biomedical NER Corpus for Relation Extraction Task","date":"2019-01-29","arxiv_id":"1901.10219","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-ner-system-for-multi-source-offer","title":"Hybrid NER System for Multi-Source Offer Feeds","date":"2019-01-24","arxiv_id":"1901.08406","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-transfer-learning-for-named-entity","title":"Dynamic Transfer Learning for Named Entity Recognition","date":"2018-12-13","arxiv_id":"1812.05288","repositories_listed":0,"syntology":null},{"url":null,"slug":"end-to-end-joint-entity-extraction-and","title":"Joint Entity Extraction and Assertion Detection for Clinical Text","date":"2018-12-13","arxiv_id":"1812.05270","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-the-importance-of-context-and","title":"Exploring the importance of context and embeddings in neural NER models for task-oriented dialogue systems","date":"2018-12-06","arxiv_id":"1812.02370","repositories_listed":0,"syntology":null},{"url":null,"slug":"pathology-extraction-from-chest-x-ray","title":"Pathology Extraction from Chest X-Ray Radiology Reports: A Performance Study","date":"2018-12-06","arxiv_id":"1812.02305","repositories_listed":0,"syntology":null},{"url":null,"slug":"inflection-tolerant-ontology-based-named","title":"Inflection-Tolerant Ontology-Based Named Entity Recognition for Real-Time Applications","date":"2018-12-05","arxiv_id":"1812.02119","repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-neural-and-knowledge-based","title":"Combining neural and knowledge-based approaches to Named Entity Recognition in Polish","date":"2018-11-26","arxiv_id":"1811.10418","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-graph-based-individual-named-entity","title":"Scalable graph-based individual named entity identification","date":"2018-11-26","arxiv_id":"1811.10547","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-sequence-labeling-for-vietnamese-pos","title":"Neural sequence labeling for Vietnamese POS Tagging and NER","date":"2018-11-09","arxiv_id":"1811.03754","repositories_listed":0,"syntology":null},{"url":null,"slug":"microner-a-micro-service-for-german-named","title":"microNER: A Micro-Service for German Named Entity Recognition based on BiLSTM-CRF","date":"2018-11-07","arxiv_id":"1811.02902","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-crf-transducers-for-sequence-labeling","title":"Neural CRF transducers for sequence labeling","date":"2018-11-04","arxiv_id":"1811.01382","repositories_listed":0,"syntology":null},{"url":null,"slug":"named-entity-recognition-on-twitter-for","title":"Named Entity Recognition on Twitter for Turkish using Semi-supervised Learning with Word Embeddings","date":"2018-10-20","arxiv_id":"1810.08732","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-script-hindi-english-ner-corpus-from","title":"Cross Script Hindi English NER Corpus from Wikipedia","date":"2018-10-08","arxiv_id":"1810.03430","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-exhaustive-model-for-nested-named-entity","title":"Deep Exhaustive Model for Nested Named Entity Recognition","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-named-entity-recognition-as-an","title":"Exploring Named Entity Recognition As an Auxiliary Task for Slot Filling in Conversational Language Understanding","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"marginal-likelihood-training-of-bilstm-crf","title":"Marginal Likelihood Training of BiLSTM-CRF for Biomedical Named Entity Recognition from Disjoint Label Sets","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"memory-show-the-way-memory-based-few-shot","title":"Memory, Show the Way: Memory Based Few Shot Word Representation Learning","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-entity-reasoner-for-global-consistency","title":"Neural Entity Reasoner for Global Consistency in NER","date":"2018-09-30","arxiv_id":"1810.00347","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-grained-entity-proposal-network-for","title":"Multi-Grained Entity Proposal Network for Named Entity Recognition","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"recognizing-film-entities-in-podcasts","title":"Recognizing Film Entities in Podcasts","date":"2018-09-24","arxiv_id":"1809.08711","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-strength-of-character-language-models","title":"On the Strength of Character Language Models for Multilingual Named Entity Recognition","date":"2018-09-13","arxiv_id":"1809.05157","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparing-cnn-and-lstm-character-level","title":"Comparing CNN and LSTM character-level embeddings in BiLSTM-CRF models for chemical and disease named entity recognition","date":"2018-08-25","arxiv_id":"1808.08450","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-named-entity-recognition-from-subword","title":"Neural Named Entity Recognition from Subword Units","date":"2018-08-22","arxiv_id":"1808.07364","repositories_listed":0,"syntology":null},{"url":null,"slug":"confidence-penalty-annealing-gaussian-noise","title":"Confidence penalty, annealing Gaussian noise and zoneout for biLSTM-CRF networks for named entity recognition","date":"2018-08-13","arxiv_id":"1808.04029","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-hassle-free-machine-learning-method-for","title":"A Hassle-Free Machine Learning Method for Cohort Selection of Clinical Trials","date":"2018-08-10","arxiv_id":"1808.04694","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-study-on-fine-grained-named","title":"An Empirical Study on Fine-Grained Named Entity Recognition","date":"2018-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"gbd-ner-at-parseme-shared-task-2018-multi","title":"GBD-NER at PARSEME Shared Task 2018: Multi-Word Expression Detection Using Bidirectional Long-Short-Term Memory Networks and Graph-Based Decoding","date":"2018-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-progressively-recognize-new-named","title":"Learning to Progressively Recognize New Named Entities with Sequence to Sequence Models","date":"2018-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-neural-sequence-labelling-using","title":"Improving Neural Sequence Labelling using Additional Linguistic Information","date":"2018-07-27","arxiv_id":"1807.10805","repositories_listed":0,"syntology":null},{"url":null,"slug":"bench-marking-information-extraction-in-semi","title":"Bench-Marking Information Extraction in Semi-Structured Historical Handwritten Records","date":"2018-07-17","arxiv_id":"1807.06270","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-named-entity-recognition-shootout-for","title":"A Named Entity Recognition Shootout for German","date":"2018-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-study-of-the-importance-of-external","title":"A Study of the Importance of External Knowledge in the Named Entity Recognition Task","date":"2018-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"bioama-towards-an-end-to-end-biomedical","title":"BioAMA: Towards an End to End BioMedical Question Answering System","date":"2018-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"biomedical-event-extraction-using","title":"Biomedical Event Extraction Using Convolutional Neural Networks and Dependency Parsing","date":"2018-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"crf-lstm-text-mining-method-unveiling-the","title":"CRF-LSTM Text Mining Method Unveiling the Pharmacological Mechanism of Off-target Side Effect of Anti-Multiple Myeloma Drugs","date":"2018-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"iit-bhu-submission-for-the-acl-shared-task-on","title":"IIT (BHU) Submission for the ACL Shared Task on Named Entity Recognition on Code-switched Data","date":"2018-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"language-identification-and-named-entity","title":"Language Identification and Named Entity Recognition in Hinglish Code Mixed Tweets","date":"2018-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multilingual-named-entity-recognition-on","title":"Multilingual Named Entity Recognition on Spanish-English Code-switched Tweets using Support Vector Machines","date":"2018-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"named-entity-tagging-and-domain-adaptation","title":"Named-Entity Tagging and Domain adaptation for Better Customized Translation","date":"2018-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"simple-features-for-strong-performance-on","title":"Simple Features for Strong Performance on Named Entity Recognition in Code-Switched Twitter Data","date":"2018-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"tackling-code-switched-ner-participation-of","title":"Tackling Code-Switched NER: Participation of CMU","date":"2018-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"character-level-feature-extraction-with","title":"Character-Level Feature Extraction with Densely Connected Networks","date":"2018-06-24","arxiv_id":"1806.09089","repositories_listed":0,"syntology":null}],"record_sha256":"7dc3d005653b4a4d25c585b2fe58192ac498b3942fbfa5da2bd2a3008e9dbfe1","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}