[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-7/)

[home](https://md.mova.elamur.ai/free/en/) / [docs](https://md.mova.elamur.ai/free/en/docs/) / [papers](https://md.mova.elamur.ai/free/en/docs/papers/) / [cited-by](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/) / Who cites «Building a Large Annotated Corpus of English: The Penn Treebank» · page 7

# Who cites «Building a Large Annotated Corpus of English: The Penn Treebank» · page 7

2515 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/bank-1993-marcus-building-large-annotated-corpus-english/)

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english/) · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-2/) · [3](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-3/) · [4](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-4/) · [5](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-5/) · [6](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-6/) · **7** · [8](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-8/) · [9](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-9/) · [10](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-10/) · [11](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-11/) · [12](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-12/) · [13](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-13/) · [14](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-14/) · [15](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-15/) · [16](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-16/) · [17](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-17/) · [18](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-18/) · [19](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-19/) · [20](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-20/) · [21](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-21/) · [22](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-22/) · [23](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-23/) · [24](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-24/) · [25](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-25/) · [26](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-26/)

1. [Spanish HPSG Treebank based on the AnCora Corpus](https://aclanthology.org/L18-1349/) *— 2018 · Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)*
2. [Spherical Latent Spaces for Stable Variational Autoencoders](https://aclanthology.org/D18-1480/) *— 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing*
3. [Stack-Pointer Networks for Dependency Parsing](https://aclanthology.org/P18-1130/) *— 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
4. [Survey: Anaphora With Non-nominal Antecedents in Computational Linguistics: a Survey](https://md.mova.elamur.ai/free/en/docs/papers/kolhatkar-2018-survey-anaphora-non-nominal-antecedents/) *— our card · 2018*
5. [TF-LM: TensorFlow-based Language Modeling Toolkit](https://aclanthology.org/L18-1470/) *— 2018 · Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)*
6. [The Hitchhiker's Guide to Testing Statistical Significance in Natural Language Processing](https://aclanthology.org/P18-1128/) *— 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
7. [The SSIX Corpora: Three Gold Standard Corpora for Sentiment Analysis in English, Spanish and German Financial Microblogs](https://aclanthology.org/L18-1423/) *— 2018 · Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)*
8. [The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks](https://arxiv.org/abs/1802.08232) *— 2018 · arXiv:1802.08232*
9. [Tools for Building an Interlinked Synonym Lexicon Network](https://aclanthology.org/L18-1136/) *— 2018 · Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)*
10. [Towards Semi-Supervised Learning for Deep Semantic Role Labeling](https://aclanthology.org/D18-1538/) *— 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing*
11. [Transferring from Formal Newswire Domain with Hypernet for Twitter POS Tagging](https://aclanthology.org/D18-1275/) *— 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing*
12. [Two Local Models for Neural Constituent Parsing](https://aclanthology.org/C18-1011/) *— 2018 · Proceedings of the 27th International Conference on Computational Linguistics*
13. [Unsupervised Discrete Sentence Representation Learning for Interpretable Neural Dialog Generation](https://aclanthology.org/P18-1101/) *— 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
14. [Unsupervised Grammar Induction with Depth-bounded PCFG](https://aclanthology.org/Q18-1016/) *— 2018 · Transactions of the Association for Computational Linguistics*
15. [Unsupervised Induction of Linguistic Categories with Records of Reading, Speaking, and Writing](https://aclanthology.org/N18-1184/) *— 2018 · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)*
16. [Unsupervised Learning of Syntactic Structure with Invertible Neural Projections](https://aclanthology.org/D18-1160/) *— 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing*
17. [Using Lexical Alignment and Referring Ability to Address Data Sparsity in Situated Dialog Reference Resolution](https://aclanthology.org/D18-1252/) *— 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing*
18. [Valency-Augmented Dependency Parsing](https://aclanthology.org/D18-1159/) *— 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing*
19. [Weighted DAG Automata for Semantic Graphs](https://aclanthology.org/J18-1005/) *— 2018 · Computational Linguistics*
20. [What can we learn from Semantic Tagging?](https://aclanthology.org/D18-1526/) *— 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing*
21. [What's Going On in Neural Constituency Parsers? An Analysis](https://aclanthology.org/N18-1091/) *— 2018 · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)*
22. [When and Why Are Pre-Trained Word Embeddings Useful for Neural Machine Translation?](https://aclanthology.org/N18-2084/) *— 2018 · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)*
23. [ZAP: An Open-Source Multilingual Annotation Projection Framework](https://aclanthology.org/L18-1344/) *— 2018 · Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)*
24. [A Comparison of Neural Models for Word Ordering](https://aclanthology.org/W17-3531/) *— 2017 · Proceedings of the 10th International Conference on Natural Language Generation*
25. [A Hybrid Convolutional Variational Autoencoder for Text Generation](https://aclanthology.org/D17-1066/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
26. [A Mention-Ranking Model for Abstract Anaphora Resolution](https://md.mova.elamur.ai/free/en/docs/papers/marasovic-2017-mention-ranking-model-abstract-anaphora/) *— our card · 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
27. [A Minimal Span-Based Neural Constituency Parser](https://aclanthology.org/P17-1076/) *— 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
28. [A Neural Architecture for Generating Natural Language Descriptions from Source Code Changes](https://aclanthology.org/P17-2045/) *— 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
29. [A Rich Morphological Tagger for English: Exploring the Cross-Linguistic Tradeoff Between Morphology and Syntax](https://md.mova.elamur.ai/free/en/docs/papers/kirov-2017-rich-morphological-tagger-english-exploring/) *— our card · 2017 · Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers*
30. [A Systematic Study of Neural Discourse Models for Implicit Discourse Relation](https://aclanthology.org/E17-1027/) *— 2017 · Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers*
31. [Adversarial Generation of Natural Language](https://aclanthology.org/W17-2629/) *— 2017 · Proceedings of the 2nd Workshop on Representation Learning for NLP*
32. [Attention Is All You Need](https://arxiv.org/abs/1706.03762) *— 2017 · arXiv:1706.03762*
33. [Autobank: a semi-automatic annotation tool for developing deep Minimalist Grammar treebanks](https://aclanthology.org/E17-3021/) *— 2017 · Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics*
34. [BENCHIP: Benchmarking Intelligence Processors](https://arxiv.org/abs/1710.08315) *— 2017 · arXiv:1710.08315*
35. [Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks](https://arxiv.org/abs/1712.01507) *— 2017 · arXiv:1712.01507*
36. [Can Discourse Relations be Identified Incrementally?](https://aclanthology.org/I17-2027/) *— 2017 · Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
37. [Classifying Semantic Clause Types: Modeling Context and Genre Characteristics with Recurrent Neural Networks and Attention](https://aclanthology.org/S17-1027/) *— 2017 · Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)*
38. [Does syntax help discourse segmentation? Not so much](https://aclanthology.org/D17-1258/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
39. [Effective Inference for Generative Neural Parsing](https://aclanthology.org/D17-1178/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
40. [Empower Sequence Labeling with Task-Aware Neural Language Model](https://arxiv.org/abs/1709.04109) *— 2017 · arXiv:1709.04109*
41. [Encoder-Decoder Shift-Reduce Syntactic Parsing](https://aclanthology.org/W17-6315/) *— 2017 · Proceedings of the 15th International Conference on Parsing Technologies*
42. [Error-repair Dependency Parsing for Ungrammatical Texts](https://aclanthology.org/P17-2030/) *— 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
43. [Exploring Joint Neural Model for Sentence Level Discourse Parsing and Sentiment Analysis](https://aclanthology.org/W17-5535/) *— 2017 · Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue*
44. [Fast(er) Exact Decoding and Global Training for Transition-Based Dependency Parsing via a Minimal Feature Set](https://aclanthology.org/D17-1002/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
45. [From Characters to Words to in Between: Do We Capture Morphology?](https://aclanthology.org/P17-1184/) *— 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
46. [GEC into the future: Where are we going and how do we get there?](https://aclanthology.org/W17-5019/) *— 2017 · Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications*
47. [Hybrid Grammars for Parsing of Discontinuous Phrase Structures and Non-Projective Dependency Structures](https://aclanthology.org/J17-3001/) *— 2017*
48. [Identifying beneficial task relations for multi-task learning in deep neural networks](https://aclanthology.org/E17-2026/) *— 2017 · Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers*
49. [Improving a Strong Neural Parser with Conjunction-Specific Features](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2017-ficler-improving-strong-neural-parser-conjunction/) *— our card · 2017 · Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers*
50. [In-Order Transition-based Constituent Parsing](https://aclanthology.org/Q17-1029/) *— 2017 · Transactions of the Association for Computational Linguistics*
51. [Joint Syntacto-Discourse Parsing and the Syntacto-Discourse Treebank](https://md.mova.elamur.ai/free/en/docs/papers/zhao-2017-joint-syntacto-discourse-parsing-syntacto/) *— our card · 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
52. [Learning to Embed Words in Context for Syntactic Tasks](https://aclanthology.org/W17-2632/) *— 2017 · Proceedings of the 2nd Workshop on Representation Learning for NLP*
53. [Learning to Generate Reviews and Discovering Sentiment](https://arxiv.org/abs/1704.01444) *— 2017 · arXiv:1704.01444*
54. [Learning to Prune: Exploring the Frontier of Fast and Accurate Parsing](https://aclanthology.org/Q17-1019/) *— 2017 · Transactions of the Association for Computational Linguistics*
55. [Measurement Context Extraction from Text: Discovering Opportunities and Gaps in Earth Science](https://arxiv.org/abs/1710.04312) *— 2017 · arXiv:1710.04312 · 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Data-Driven Discovery Workshop, Halifax, Canada, August 2017*
56. [Morphology-based Entity and Relational Entity Extraction Framework for Arabic](https://aclanthology.org/2017.tal-3.6/) *— 2017*
57. [Neural Discourse Structure for Text Categorization](https://aclanthology.org/P17-1092/) *— 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
58. [Neural Language Modeling by Jointly Learning Syntax and Lexicon](https://arxiv.org/abs/1711.02013) *— 2017 · arXiv:1711.02013*
59. [Neural Probabilistic Model for Non-projective MST Parsing](https://aclanthology.org/I17-1007/) *— 2017 · Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
60. [On the State of the Art of Evaluation in Neural Language Models](https://arxiv.org/abs/1707.05589) *— 2017 · arXiv:1707.05589*
61. [Parser Adaptation for Social Media by Integrating Normalization](https://aclanthology.org/P17-2078/) *— 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
62. [Part-of-Speech Tagging for Twitter with Adversarial Neural Networks](https://aclanthology.org/D17-1256/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
63. [Predicting Native Language from Gaze](https://aclanthology.org/P17-1050/) *— 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
64. [Regularizing Neural Networks by Penalizing Confident Output Distributions](https://arxiv.org/abs/1701.06548) *— 2017 · arXiv:1701.06548*
65. [Replicability Analysis for Natural Language Processing: Testing Significance with Multiple Datasets](https://aclanthology.org/Q17-1033/) *— 2017*
66. [Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging](https://aclanthology.org/D17-1035/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
67. [Représentation et analyse automatique des discontinuités syntaxiques dans les corpus arborés en constituants du français (Representation and parsing of syntactic discontinuities in French constituent treebanks)](https://aclanthology.org/2017.jeptalnrecital-long.6/) *— 2017 · Actes des 24ème Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 - Articles longs*
68. [Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling](https://aclanthology.org/P17-1030/) *— 2017 · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
69. [Shift-Reduce Constituent Parsing with Neural Lookahead Features](https://aclanthology.org/Q17-1004/) *— 2017 · Transactions of the Association for Computational Linguistics*
70. [Signalling Implicit Relations: A PDTB - RST Comparison](https://journals.uic.edu/ojs/index.php/dad/article/view/10787) *— 2017 · Dialogue & Discourse*
71. [Sparse Coding of Neural Word Embeddings for Multilingual Sequence Labeling](https://aclanthology.org/Q17-1018/) *— 2017 · Transactions of the Association for Computational Linguistics*
72. [Stack-based Multi-layer Attention for Transition-based Dependency Parsing](https://aclanthology.org/D17-1175/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
73. [Structured Prediction via Learning to Search under Bandit Feedback](https://aclanthology.org/W17-4304/) *— 2017 · Proceedings of the 2nd Workshop on Structured Prediction for Natural Language Processing*
74. [Survey: Multiword Expression Processing: A Survey](https://aclanthology.org/J17-4005/) *— 2017*
75. [Syllable-aware Neural Language Models: A Failure to Beat Character-aware Ones](https://aclanthology.org/D17-1199/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
76. [Towards Universal Semantic Tagging](https://aclanthology.org/W17-6901/) *— 2017 · Proceedings of the 12th International Conference on Computational Semantics (IWCS) –- Short papers*
77. [Transition-Based Disfluency Detection using LSTMs](https://aclanthology.org/D17-1296/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
78. [Transition-Based Generation from Abstract Meaning Representations](https://arxiv.org/abs/1707.07591) *— 2017 · arXiv:1707.07591*
79. [Translation Divergences in Chinese–English Machine Translation: An Empirical Investigation](https://md.mova.elamur.ai/free/en/docs/papers/deng-2017-translation-divergences-chinese-english-machine/) *— our card · 2017 · Computational Linguistics*
80. [UCCAApp: Web-application for Syntactic and Semantic Phrase-based Annotation](https://aclanthology.org/P17-4019/) *— 2017 · Proceedings of ACL 2017, System Demonstrations*
81. [Universal Dependencies for Arabic](https://md.mova.elamur.ai/free/en/docs/papers/ud-2017-taji-universal-dependencies-arabic/) *— our card · 2017 · Proceedings of the Third Arabic Natural Language Processing Workshop*
82. [Universal Dependencies for Serbian in Comparison with Croatian and Other Slavic Languages](https://aclanthology.org/W17-1407/) *— 2017 · Proceedings of the 6th Workshop on Balto-Slavic Natural Language Processing*
83. [Universal Semantic Parsing](https://aclanthology.org/D17-1009/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
84. [Using the Output Embedding to Improve Language Models](https://aclanthology.org/E17-2025/) *— 2017 · Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers*
85. [When does a compliment become sexist? Analysis and classification of ambivalent sexism using twitter data](https://aclanthology.org/W17-2902/) *— 2017 · Proceedings of the Second Workshop on NLP and Computational Social Science*
86. [A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks](https://arxiv.org/abs/1610.02136) *— 2016 · arXiv:1610.02136 · International Conference on Learning Representations 2017*
87. [A Discourse-Annotated Corpus of Conjoined VPs](https://aclanthology.org/W16-1704/) *— 2016 · Proceedings of the 10th Linguistic Annotation Workshop held in conjunction with ACL 2016 (LAW-X 2016)*
88. [A Neural Knowledge Language Model](https://arxiv.org/abs/1608.00318) *— 2016 · arXiv:1608.00318*
89. [A Search-Based Dynamic Reranking Model for Dependency Parsing](https://aclanthology.org/P16-1132/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
90. [A Universal Framework for Inductive Transfer Parsing across Multi-typed Treebanks](https://aclanthology.org/C16-1002/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*
91. [Anchoring and Agreement in Syntactic Annotations](https://aclanthology.org/D16-1239/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
92. [Attending to Characters in Neural Sequence Labeling Models](https://aclanthology.org/C16-1030/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*
93. [Automatic Cross-Lingual Similarization of Dependency Grammars for Tree-based Machine Translation](https://md.mova.elamur.ai/free/en/docs/papers/jiang-2016-automatic-cross-lingual-similarization-dependency/) *— our card · 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
94. [Bootstrapped Text-level Named Entity Recognition for Literature](https://aclanthology.org/P16-2056/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
95. [Building A Case-based Semantic English-Chinese Parallel Treebank](https://aclanthology.org/L16-1466/) *— 2016 · Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)*
96. [Capturing Pragmatic Knowledge in Article Usage Prediction using LSTMs](https://aclanthology.org/C16-1247/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*
97. [Combining Ontologies and Neural Networks for Analyzing Historical Language Varieties. A Case Study in Middle Low German](https://aclanthology.org/L16-1234/) *— 2016 · Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)*
98. [Coordination Annotation Extension in the Penn Tree Bank](https://aclanthology.org/P16-1079/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
99. [Correlation-based Intrinsic Evaluation of Word Vector Representations](https://aclanthology.org/W16-2520/) *— 2016 · Proceedings of the 1st Workshop on Evaluating Vector-Space Representations for NLP*
100. [Crowdsourcing Complex Language Resources: Playing to Annotate Dependency Syntax](https://aclanthology.org/C16-1286/) *— 2016 · Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers*

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english/) · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-2/) · [3](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-3/) · [4](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-4/) · [5](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-5/) · [6](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-6/) · **7** · [8](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-8/) · [9](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-9/) · [10](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-10/) · [11](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-11/) · [12](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-12/) · [13](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-13/) · [14](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-14/) · [15](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-15/) · [16](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-16/) · [17](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-17/) · [18](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-18/) · [19](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-19/) · [20](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-20/) · [21](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-21/) · [22](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-22/) · [23](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-23/) · [24](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-24/) · [25](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-25/) · [26](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-26/)

- [← previous Who cites «Building a Large Annotated Corpus of English: The Penn Treebank» · page 6](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-6/)
- [next → Who cites «Building a Large Annotated Corpus of English: The Penn Treebank» · page 8](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/bank-1993-marcus-building-large-annotated-corpus-english-8/)
- [↑ back to papers/cited-by/](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/)