{"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/constituency-parsing/papers/2","list_of":"/task/constituency-parsing","task":"Constituency Parsing","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":2,"pages_in_order":3,"rows_per_page":100,"rows":[101,200],"of":204,"counts":{"archive_papers_tagged":204,"with_a_code_link":81,"where_syntology_ran_a_sample":24,"not_listed_spam_title":0,"listed":204,"listed_where_code_ran":24,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":21,"every_run_a_failure_of_syntologys_instrument":3,"listed_with_a_run_with_no_instrument_failure":21,"listed_every_run_a_failure_of_syntologys_instrument":3,"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/constituency-parsing","prev":"/task/constituency-parsing","next":"/task/constituency-parsing/papers/3","papers":[{"url":null,"slug":"investigating-non-local-features-for-neural-1","title":"Investigating Non-local Features for Neural Constituency Parsing","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-full-constituency-parsing-with-1","title":"Unsupervised Full Constituency Parsing with Neighboring Distribution Divergence","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-warm-start-and-a-clean-crawled-corpus-a","title":"A Warm Start and a Clean Crawled Corpus -- A Recipe for Good Language Models","date":"2022-01-14","arxiv_id":"2201.05601","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantics-preserved-distortion-for-personal","title":"Semantics-Preserved Distortion for Personal Privacy Protection in Information Management","date":"2022-01-04","arxiv_id":"2201.00965","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-source-cross-lingual-constituency","title":"Multi-Source Cross-Lingual Constituency Parsing","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nested-named-entity-recognition-as-latent","title":"Nested Named Entity Recognition as Latent Lexicalized Constituency Parsing","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"phrase-aware-unsupervised-constituency","title":"Phrase-aware Unsupervised Constituency Parsing","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"re-thinking-supertags-in-linear-context-free","title":"Re-thinking Supertags in Linear Context-free Rewriting Systems for Constituency Parsing","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-full-constituency-parsing-with","title":"Unsupervised Full Constituency Parsing with Neighboring Distribution Divergence","date":"2021-10-29","arxiv_id":"2110.15931","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-lingual-constituency-parsing-with","title":"Cross-lingual Constituency Parsing with Linguistic Typology Knowledge","date":"2021-10-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"self-attentive-constituency-parsing-for-ucca","title":"Self-Attentive Constituency Parsing for UCCA-based Semantic Parsing","date":"2021-10-01","arxiv_id":"2110.00621","repositories_listed":0,"syntology":null},{"url":null,"slug":"universal-recurrent-neural-network-grammar","title":"Universal Recurrent Neural Network Grammar","date":"2021-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-machine-translation-with-synchronous","title":"Neural Machine Translation with Synchronous Latent Phrase Structure","date":"2021-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-conditional-splitting-framework-for","title":"A Conditional Splitting Framework for Efficient Constituency Parsing","date":"2021-06-30","arxiv_id":"2106.15760","repositories_listed":0,"syntology":null},{"url":null,"slug":"recursive-tree-attention-improving-semantic","title":"Recursive Tree Attention: Improving Semantic Representations with Syntactic Tree Structured Attention Mechanism","date":"2021-06-04","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-limitations-of-limited-context-for","title":"The Limitations of Limited Context for Constituency Parsing","date":"2021-06-03","arxiv_id":"2106.01580","repositories_listed":0,"syntology":null},{"url":null,"slug":"rl-grit-reinforcement-learning-for-grammar","title":"RL-GRIT: Reinforcement Learning for Grammar Inference","date":"2021-05-17","arxiv_id":"2105.13114","repositories_listed":0,"syntology":null},{"url":null,"slug":"genres-parsers-and-bert-the-interaction","title":"Genres, Parsers, and BERT: The Interaction Between Parsers and BERT Models in Cross-Genre Constituency Parsing in English and Swedish","date":"2021-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-evolution-of-syntactic-information","title":"On the Evolution of Syntactic Information Encoded by BERT's Contextualized Representations","date":"2021-01-27","arxiv_id":"2101.11492","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-inside-outside-recursive-autoencoder","title":"Deep Inside-outside Recursive Autoencoder with All-span Objective","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"span-based-discontinuous-constituency-parsing-1","title":"Span-based discontinuous constituency parsing: a family of exact chart-based algorithms with time complexities from O(n\\^6) down to O(n\\^3)","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/unsupervised-parsing-with-s-diora-single-tree","slug":"unsupervised-parsing-with-s-diora-single-tree","title":"Unsupervised Parsing with S-DIORA: Single Tree Encoding for Deep Inside-Outside Recursive Autoencoders","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-study-for-vietnamese","title":"An Empirical Study for Vietnamese Constituency Parsing with Pre-training","date":"2020-10-19","arxiv_id":"2010.09623","repositories_listed":0,"syntology":null},{"url":null,"slug":"heads-up-unsupervised-constituency-parsing","title":"Heads-up! Unsupervised Constituency Parsing via Self-Attention Heads","date":"2020-10-19","arxiv_id":"2010.09517","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-role-of-supervision-in-unsupervised","title":"On the Role of Supervision in Unsupervised Constituency Parsing","date":"2020-10-06","arxiv_id":"2010.02423","repositories_listed":0,"syntology":null},{"url":null,"slug":"reusable-phrase-extraction-based-on-syntactic","title":"Reusable Phrase Extraction Based on Syntactic Parsing","date":"2020-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-comparison-of-unsupervised","title":"An Empirical Comparison of Unsupervised Constituency Parsing Methods","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-constituency-parsing-by-pointing-1","title":"Efficient Constituency Parsing by Pointing","date":"2020-06-24","arxiv_id":"2006.13557","repositories_listed":0,"syntology":null},{"url":null,"slug":"qu-apporte-bert-a-l-analyse-syntaxique-en","title":"Qu'apporte BERT \\`a l'analyse syntaxique en constituants discontinus ? Une suite de tests pour \\'evaluer les pr\\'edictions de structures syntaxiques discontinues en anglais (What does BERT contribute to discontinuous constituency parsing ? A test suite to evaluate discontinuous constituency structure predictions in English)","date":"2020-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"at-which-level-should-we-extract-an-empirical","title":"At Which Level Should We Extract? An Empirical Analysis on Extractive Document Summarization","date":"2020-04-06","arxiv_id":"2004.02664","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-syntactic-and-dynamic-selective","title":"Learning Syntactic and Dynamic Selective Encoding for Document Summarization","date":"2020-03-25","arxiv_id":"2003.11173","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-constituency-parsing-tree-based-method-for","title":"A Constituency Parsing Tree based Method for Relation Extraction from Abstracts of Scholarly Publications","date":"2019-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-general-purpose-algorithm-for-constrained","title":"A General-Purpose Algorithm for Constrained Sequential Inference","date":"2019-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-labeled-parsing-with-deep-inside","title":"Unsupervised Labeled Parsing with Deep Inside-Outside Recursive Autoencoders","date":"2019-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-constituency-parsing-of-speech","title":"Neural Constituency Parsing of Speech Transcripts","date":"2019-04-17","arxiv_id":"1904.08535","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":"investigating-np-chunking-with-universal","title":"Investigating NP-Chunking with Universal Dependencies for English","date":"2018-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-parsing-for-task-oriented-dialog","title":"Semantic Parsing for Task Oriented Dialog using Hierarchical Representations","date":"2018-10-18","arxiv_id":"1810.07942","repositories_listed":0,"syntology":null},{"url":null,"slug":"top-down-tree-structured-decoding-with","title":"Top-down Tree Structured Decoding with Syntactic Connections for Neural Machine Translation and Parsing","date":"2018-09-06","arxiv_id":"1809.01854","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-investigation-of-error-types-in","title":"An Empirical Investigation of Error Types in Vietnamese Parsing","date":"2018-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"policy-gradient-as-a-proxy-for-dynamic","title":"Policy Gradient as a Proxy for Dynamic Oracles in Constituency Parsing","date":"2018-06-08","arxiv_id":"1806.03290","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-dependency-perspective-on-rst-discourse","title":"A Dependency Perspective on RST Discourse Parsing and Evaluation","date":"2018-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dialog-generation-using-multi-turn-reasoning","title":"Dialog Generation Using Multi-Turn Reasoning Neural Networks","date":"2018-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ynu-deep-at-semeval-2018-task-12-a-bilstm","title":"YNU Deep at SemEval-2018 Task 12: A BiLSTM Model with Neural Attention for Argument Reasoning Comprehension","date":"2018-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"linear-time-constituency-parsing-with-rnns","title":"Linear-Time Constituency Parsing with RNNs and Dynamic Programming","date":"2018-05-17","arxiv_id":"1805.06995","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-new-version-of-the-skaadnica-treebank-of","title":"A New Version of the Sk\\ladnica Treebank of Polish Harmonised with the Walenty Valency Dictionary","date":"2018-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"coreference-resolution-in-freeling-40","title":"Coreference Resolution in FreeLing 4.0","date":"2018-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"attentive-tensor-product-learning","title":"Attentive Tensor Product Learning","date":"2018-02-20","arxiv_id":"1802.07089","repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-attention-for-sequence-to-sequence","title":"Supervised Attention for Sequence-to-Sequence Constituency Parsing","date":"2017-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"optimizing-for-measure-of-performance-in-max","title":"Optimizing for Measure of Performance in Max-Margin Parsing","date":"2017-09-05","arxiv_id":"1709.01562","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-discontinuous-constituency-parsing","title":"Neural Discontinuous Constituency Parsing","date":"2017-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unity-in-diversity-a-unified-parsing-strategy","title":"Unity in Diversity: A Unified Parsing Strategy for Major Indian Languages","date":"2017-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-generative-parser-with-a-discriminative","title":"A Generative Parser with a Discriminative Recognition Algorithm","date":"2017-08-01","arxiv_id":"1708.00415","repositories_listed":0,"syntology":null},{"url":null,"slug":"effective-inference-for-generative-neural","title":"Effective Inference for Generative Neural Parsing","date":"2017-07-27","arxiv_id":"1707.08976","repositories_listed":0,"syntology":null},{"url":null,"slug":"gradient-based-inference-for-networks-with","title":"Gradient-based Inference for Networks with Output Constraints","date":"2017-07-26","arxiv_id":"1707.08608","repositories_listed":0,"syntology":null},{"url":"/paper/improving-neural-parsing-by-disentangling","slug":"improving-neural-parsing-by-disentangling","title":"Improving Neural Parsing by Disentangling Model Combination and Reranking Effects","date":"2017-07-10","arxiv_id":"1707.03058","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-minimal-span-based-neural-constituency","title":"A Minimal Span-Based Neural Constituency Parser","date":"2017-05-10","arxiv_id":"1705.03919","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-prune-exploring-the-frontier-of","title":"Learning to Prune: Exploring the Frontier of Fast and Accurate Parsing","date":"2017-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"temporalodil-project-adapting-iso-timeml-to","title":"Temporal@ODIL project: Adapting ISO-TimeML to syntactic treebanks for the temporal annotation of spoken speech","date":"2017-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-for-efficient-model-selection-for","title":"Boosting for Efficient Model Selection for Syntactic Parsing","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-neural-translation-models-with","title":"Improving Neural Translation Models with Linguistic Factors","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"incremental-parsing-with-minimal-features","title":"Incremental Parsing with Minimal Features Using Bi-Directional LSTM","date":"2016-06-21","arxiv_id":"1606.06406","repositories_listed":0,"syntology":null},{"url":null,"slug":"discontinuity-re-visited-a-minimalist","title":"Discontinuity (Re)\\mbox$^2$-visited: A Minimalist Approach to Pseudoprojective Constituent Parsing","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"construction-of-an-english-dependency-corpus","title":"Construction of an English Dependency Corpus incorporating Compound Function Words","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"statistical-parsing-by-machine-learning-from","title":"Statistical Parsing by Machine Learning from a Classical Arabic Treebank","date":"2015-10-25","arxiv_id":"1510.07193","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-confidence-based-self-training-for","title":"Exploring Confidence-based Self-training for Multilingual Dependency Parsing in an Under-Resourced Language Scenario","date":"2015-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-for-dependency-parsing-via","title":"Domain Adaptation for Dependency Parsing via Self-Training","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"identifying-cascading-errors-using","title":"Identifying Cascading Errors using Constraints in Dependency Parsing","date":"2015-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deepnl-a-deep-learning-nlp-pipeline","title":"DeepNL: a Deep Learning NLP pipeline","date":"2015-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"shift-reduce-constituency-parsing-with","title":"Shift-Reduce Constituency Parsing with Dynamic Programming and POS Tag Lattice","date":"2015-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-effect-of-dependency-representation","title":"The Effect of Dependency Representation Scheme on Syntactic Language Modelling","date":"2014-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-fast-and-accurate-dependency-parser-using","title":"A Fast and Accurate Dependency Parser using Neural Networks","date":"2014-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"left-corner-transitions-on-dependency-parsing","title":"Left-corner Transitions on Dependency Parsing","date":"2014-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"chunking-clinical-text-containing-non","title":"Chunking Clinical Text Containing Non-Canonical Language","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"how-much-do-word-embeddings-encode-about","title":"How much do word embeddings encode about syntax?","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"strategies-for-contiguous-multiword","title":"Strategies for Contiguous Multiword Expression Analysis and Dependency Parsing","date":"2014-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"constituency-parsing-of-bulgarian-word-vs","title":"Constituency Parsing of Bulgarian: Word- vs Class-based Parsing","date":"2014-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"discosuite-a-parser-test-suite-for-german","title":"Discosuite - A parser test suite for German discontinuous structures","date":"2014-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"self-training-a-constituency-parser-using-n","title":"Self-training a Constituency Parser using n-gram Trees","date":"2014-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-teraflop-constituency-parser-using","title":"A Multi-Teraflop Constituency Parser using GPUs","date":"2013-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"online-learning-for-inexact-hypergraph-search","title":"Online Learning for Inexact Hypergraph Search","date":"2013-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"representation-of-morphosyntactic-units-and","title":"Representation of Morphosyntactic Units and Coordination Structures in the Turkish Dependency Treebank","date":"2013-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"reranking-meets-morphosyntax-state-of-the-art","title":"(Re)ranking Meets Morphosyntax: State-of-the-art Results from the SPMRL 2013 Shared Task","date":"2013-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-ligm-alpage-architecture-for-the-spmrl","title":"The LIGM-Alpage architecture for the SPMRL 2013 Shared Task: Multiword Expression Analysis and Dependency Parsing","date":"2013-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"bilingually-guided-monolingual-dependency","title":"Bilingually-Guided Monolingual Dependency Grammar Induction","date":"2013-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dependency-parser-adaptation-with-subtrees","title":"Dependency Parser Adaptation with Subtrees from Auto-Parsed Target Domain Data","date":"2013-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"iterative-transformation-of-annotation","title":"Iterative Transformation of Annotation Guidelines for Constituency Parsing","date":"2013-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"parsing-russian-a-hybrid-approach","title":"Parsing Russian: a hybrid approach","date":"2013-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"part-of-speech-induction-in-dependency-trees","title":"Part-of-Speech Induction in Dependency Trees for Statistical Machine Translation","date":"2013-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"syntactic-identification-of-occurrences-of","title":"Syntactic Identification of Occurrences of Multiword Expressions in Text using a Lexicon with Dependency Structures","date":"2013-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-sources-for-constituent-parsing-of","title":"Knowledge Sources for Constituent Parsing of German, a Morphologically Rich and Less-Configurational Language","date":"2013-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"word-segmentation-unknown-word-resolution-and","title":"Word Segmentation, Unknown-word Resolution, and Morphological Agreement in a Hebrew Parsing System","date":"2013-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-lexical-dependencies-from-large","title":"Exploiting Lexical Dependencies from Large-Scale Data for Better Shift-Reduce Constituency Parsing","date":"2012-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-french-social-media-bank-a-treebank-of","title":"The French Social Media Bank: a Treebank of Noisy User Generated Content","date":"2012-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-feature-rich-constituent-context-model-for","title":"A Feature-Rich Constituent Context Model for Grammar Induction","date":"2012-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-investigation-of-statistical","title":"An Empirical Investigation of Statistical Significance in NLP","date":"2012-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"assigning-deep-lexical-types-using-structured","title":"Assigning Deep Lexical Types Using Structured Classifier Features for Grammatical Dependencies","date":"2012-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"discriminative-strategies-to-integrate","title":"Discriminative Strategies to Integrate Multiword Expression Recognition and Parsing","date":"2012-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fbk-machine-translation-evaluation-and-word","title":"FBK: Machine Translation Evaluation and Word Similarity metrics for Semantic Textual Similarity","date":"2012-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"msr-splat-a-language-analysis-toolkit","title":"MSR SPLAT, a language analysis toolkit","date":"2012-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"66a04dcd899b3d479cb0a6822d5a76eb16d84779a10e64ccf5ef3b7ff89aaddc","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}