Notes:
Coreference is a phenomenon that occurs in natural language when two or more expressions in a text refer to the same person, place, or thing. This can be seen in sentences such as “The boy was playing with his dog. He threw a ball for the dog to fetch,” where the pronoun “he” and the noun phrase “the boy” refer to the same person.
In the context of natural language processing, coreference resolution is the process of identifying and disambiguating these references in a text. This can involve techniques such as identifying pronouns and other words that are likely to refer to a previously mentioned person or thing, and using context and other information to determine the intended referent.
Coreference resolution is an important task in natural language processing, as it allows systems to better understand and interpret the meaning of a text. For example, in a dialog system, coreference resolution can be used to understand when a user is referring to a specific person or thing that was mentioned earlier in the conversation, and to generate more appropriate and relevant responses.
A coreference resolver is a natural language processing tool that identifies and replaces words or phrases in a text that refer to the same entity. For example, in the sentence “John went to the store. He bought some milk,” the pronouns “He” and “John” refer to the same person, and a coreference resolver would identify and replace “He” with “John” in the second sentence. Coreference resolution is a difficult problem in natural language processing because it requires understanding the relationships between words and entities in a text and how those relationships change over the course of the text.
Coreference resolvers are used in natural language analysis to improve the accuracy and efficiency of a range of natural language processing tasks. Here are some examples of how coreference resolvers can be used:
- Information extraction: Coreference resolution can help identify and extract key information from a text by disambiguating words and phrases that refer to the same entity.
- Text summarization: Coreference resolution can help identify the most important entities in a text and generate a summary that focuses on those entities.
- Text classification: Coreference resolution can help identify the key themes and topics of a text, which can be useful for classification tasks.
- Machine translation: Coreference resolution can help improve the accuracy of machine translation by ensuring that words and phrases are translated consistently throughout a text.
- Dialogue systems: Coreference resolution can help improve the coherence and naturalness of responses generated by a dialogue system by ensuring that words and phrases are used consistently.
Resources:
- corenlp .. a set of natural language analysis tools
- pkde4j .. entity and relation extraction for public knowledge discovery
Wikipedia:
- Coreference: Coreference resolution
- International Conference on Intelligent Text Processing and Computational Linguistics
References:
- Advanced Applications of Natural Language Processing for Performing Information Extraction (2015)
- Context-specific Consistencies in Information Extraction: Rule-based and Probabilistic Approaches (2015)
- Natural Language Processing with Java (2015)
See also:
Stanford CoreNLP & Chatbots 2019
Party Identification of Legal Documents using Co-reference Resolution and Named Entity Recognition
C Samarawickrama, M de Almeida… – 2020 IEEE 15th …, 2020 – ieeexplore.ieee.org
… IV. EXPERIMENTS A. Setup Natural Language Software: All experiments are run using the Stanford CoreNLP tools. Tools for NER, co-reference resolution and dependency parsing were specifically used within our models to come up with the presented results …
Aspect Level Sentiment Analysis Methods Applied to Text in Formal Military Reports
II Mestric, A Kok, G Valiyev, M Street… – Information & …, 2020 – connections-qj.org
… Co-reference resolution is an important step for higher level NLP tasks that involve natural language understanding such as document … For our implementation we used the Stanford CoreNLP implementation called CorefAnnotater.6 The CorefAnnotator finds mentions of the …
Rule-Based Approach for Party-Based SentimentAnalysis in Legal Opinion Texts
I Rajapaksha, CR Mudalige, D Karunarathna… – arXiv preprint arXiv …, 2020 – arxiv.org
… Stanford Co-reference Resolution model is used due to its proven performance over many NLP tasks. B. Generating sub sentences We used the constituency parser of Stanford CoreNLP [6] for the process of generating sub sentences. Legal documents …
Man is to person as woman is to location: Measuring gender bias in named entity recognition
N Mehrabi, T Gowda, F Morstatter, N Peng… – Proceedings of the 31st …, 2020 – dl.acm.org
… the analysis of gender stereotyping in different natural language processing (NLP) components, such as word embedding, co-reference resolution, machine translation … 1: Examples of PERSON entities that are wrongfully tagged as non-PERSON or NULL entities by CoreNLP …
Story Analysis Using Natural Language Processing and Interactive Dashboards
M Mitri – Journal of Computer Information Systems, 2020 – Taylor & Francis
… that there are powerful open source APIs available, such as Apache’s OpenNLP, 7 software tools from the Berkeley Natural Language Processing group, 8 and Stanford’s CoreNLP annotators … Co-reference resolution – finding all expressions that refer to the same entity in a text …
Evaluation Dataset for Zero Pronoun in Japanese to English Translation
S Shimazu, S Takase, T Nakazawa… – Proceedings of The 12th …, 2020 – aclweb.org
… Le Nagard, R. and Koehn, P. (2010). Aiding pronoun translation with co-reference resolution. In Proceedings of the Joint Fifth Workshop on Statistical Machine Trans- lation and MetricsMATR, pages 252–261 … The stanford corenlp nat- ural language processing toolkit …
From Algebraic Word Problem to Program: A Formalized Approach
A Wiemerslage, SR Ahmed – arXiv preprint arXiv:2003.11517, 2020 – arxiv.org
… addr[a] : num num[n] : num e1 : num e2 : num plus(e1;e2) : num e1 : num e2 : num minus(e1;e2) : num c : ok e : num set[a](e) ok skip ok c1 ok c2 ok seq(c1;c2) ok e : num get(e) ok 4 Page 5. Figure 5: A Co-reference resolution for Example 1 using Stanford CoreNLP Syntax chart …
VTKEL: a resource for visual-textual-knowledge entity linking
S Dost, L Serafini, M Rospocher, L Ballan… – Proceedings of the 35th …, 2020 – dl.acm.org
… to a knowledge base (ontology)[22]; • visual entity linking to a knowledge base (ontology) [25]; • visual and textual co-reference resolution [11–13 … tions is obtained by running and combining the outputs of several state-of-the-art NLP tools, including Stanford CoreNLP7 (tokeniza …
A neural entity coreference resolution review
N Stylianou, I Vlahavas – Expert Systems with Applications, 2021 – Elsevier
PharmKE: Knowledge Extraction Platform for Pharmaceutical Texts using Transfer Learning
N Jofche, K Mishev, R Stojanov, M Jovanovik… – arXiv preprint arXiv …, 2021 – arxiv.org
… Conclusions: PharmKE is a modular platform which incorporates state-of-the-art models for text categorization, pharmaceutical domain named entity recognition, co-reference resolution, semantic role labeling and knowledge extraction …
WebRED: Effective Pretraining And Finetuning For Relation Extraction On The Web
R Ormandi, M Saleh, E Winter, V Rao – arXiv preprint arXiv:2102.09681, 2021 – arxiv.org
… We perform Named Entity Recognition (NER) and Co-reference Resolution (CoRef) on every document in our text corpus2. If there are … However, there are publicly available alternatives such as: https: //stanfordnlp.github.io/CoreNLP/, https:// github.com/huggingface/neuralcoref …
SPIDER: Selective Plotting of Interconnected Data and Entity Relations
P Addepalli, E Wu, D Bossart, C Lin, A Smith – arXiv preprint arXiv …, 2020 – arxiv.org
… accessed via a web browser, and has three major components: (1) a Java API that reads documents, extracts entities and relationships using Stanford CoreNLP, (2) a … As a re- sult, co-reference resolution combines entities by merging duplicates entities into a single instance …
The role of reentrancies in abstract meaning representation parsing
M Damonte, I Szubert, SB Cohen… – Proceedings of the 2020 …, 2020 – aclweb.org
… nodes.3 Heuristics based on Universal Dependency (UD) parses (Manning et al., 2014) and automatic co- reference resolution are applied … representing government; special frames for roles 3https://github.com/jflanigan/jamr 4https://stanfordnlp.github.io/CoreNLP 5https://github …
Improving NER Performance by Applying Text Summarization on Pharmaceutical Articles
J Dobreva, N Jofche, M Jovanovik… – … Conference on ICT …, 2020 – Springer
… Through our pipeline comprised of NER, co-reference resolution and SRL, we were able to prove this hypothesis over a dataset of 1,500 articles … Manning, C., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S., McClosky, D.: The stanford CoreNLP natural language processing toolkit …
Declarative Knowledge Extraction in the AC&NL Tutor
A Grubiši?, S Stankov, B Žitko, I Šari?-Grgi?… – … Conference on Human …, 2020 – Springer
… The Stanford CoreNLP 3.8 (stanfordnlp.github.io/CoreNLP/index.html) is used for lemmatization, part-of-speech tagging, named … which the ReaderBench framework utilizes all of the above-mentioned NLP processes, but dependency parsing, co-reference resolution and named …
Legal Party Extraction from Legal Opinion Text with Sequence to Sequence Learning
M de Almeida, C Samarawickrama… – … on Advances in ICT …, 2020 – ieeexplore.ieee.org
… IV. EXPERIMENTS A. Setup Natural Language Software: All experiments are run using the Stanford CoreNLP tools. Tools for NER and co reference resolution were specifically used within our models to come up with the presented results …
WEXEA: Wikipedia EXhaustive Entity Annotation
M Strobl, A Trabelsi, OR Zaiane – … of The 12th Language Resources and …, 2020 – aclweb.org
… 3. Co-reference Resolution (CR) (Lee et al., 2018): Find- ing mentions of entities in text that refer to named en- tities, such as he, she, it or the company, the prince. 4. Relation Extraction (RE) (Takanobu et al., 2019): Finding …
Different valuable tools for Arabic sentiment analysis: a comparative evaluation.
Y Zahidi, Y El Younoussi… – International Journal of …, 2021 – pdfs.semanticscholar.org
… It is a Java annotation pipeline framework that provides language processing tasks and offers most of the common essential NLP steps, from tokenization through to co-reference resolution [21]. Stanford CoreNLP’s purpose is to make it simple to apply a bunch of linguistic …
Tools and Methodology for Converting Natural Language into RDF Representations
O Loia, E Kamateri, PD Vasileiadis – academia.edu
… These include co-reference resolution, named entity recognition and classification, entity linking and semantic annotation, and finally term and relation extraction … 2016, pp. 354–361. [2] CD Manning, J. Bauer, J. Finkel, and SJ Bethard, “The Stanford CoreNLP Natural Language …
ATHENA++ natural language querying for complex nested SQL queries
J Sen, C Lei, A Quamar, F Özcan, V Efthymiou… – Proceedings of the …, 2020 – dl.acm.org
… Operation Annotator leverages Stanford CoreNLP [24] for to- kenization and annotating dependencies between tokens in the NL query … To discover such salient information, we first employ the open source Stanford CoreNLP [24] to tokenize and parse the input NL query …
Rule-based extraction of family history information from clinical notes
JR Almeida, S Matos – Proceedings of the 35th Annual ACM Symposium …, 2020 – dl.acm.org
… Thus, those entities have also been discarded. 3.2 Dependency parsing rules For this first approach, we pre-processed the documents with Stan- ford CoreNLP [12] using the dependency parsing and co-reference resolution steps …
Enhance Trend Extraction Results by Refining with Additional Criteria
ET Khaing, MM Thein, MM Lwin – International Conference on …, 2020 – Springer
… Stanford CoreNLP and Apache OpenNLP tools don’t support to identify main verb on news contents but they classify POS tags for verb … In computational linguistics, co-reference resolution [11] refers to resolving references used within the text with a same sense …
Extraction of a knowledge graph from French cultural heritage documents
E Marchand, M Gagnon, A Zouaq – ADBIS, TPDL and EDA 2020 Common …, 2020 – Springer
… classification of heritage according to its category (House, Church, etc.) but also to complete the previous co-reference resolution module by … Manning, CD, Surdeanu, M., Bauer, J., Finkel, JR, Bethard, S., McClosky, D.: The Stanford CoreNLP natural language processing toolkit …
Declarative Knowledge Extraction in the AC&NL Tutor
I Šari?-Grgi?, A Gašpar, S Tomaš… – … Conference, AIS 2020 …, 2020 – books.google.com
… io/CoreNLP/index … Unlike the work of Panaite et al.[11], in which the ReaderBench framework utilizes all of the above-mentioned NLP processes, but dependency parsing, co-reference resolution and named entity recognition were found redundant, and thus removed to reduce …
KGen: a knowledge graph generator from biomedical scientific literature
A Rossanez, JC Dos Reis… – BMC Medical …, 2020 – bmcmedinformdecismak …
Knowledge is often produced from data generated in scientific investigations. An ever-growing number of scientific studies in several domains result into a massive amount of data, from which obtaining new knowledge requires computational help. For example, Alzheimer’s Disease …
Summarizing Opinions with Sentiment Analysis from Multiple Reviews on Travel Destinations
ARS Halder, SGS Banerjee… – … in Research and Practice …, 2020 – books.google.com
… The server 2 simplify by conjunction removal and co-reference resolution of the input text … Even if we used an example on a person?Narendra Modi, the process is similar for any location or organizations also and entirely depended the performance of Stanford coreNlp tool …
The Role of Reentrancies in Abstract Meaning Representation Parsing
I Szubert, M Damonte, SB Cohen, M Steedman – homepages.inf.ed.ac.uk
… nodes.3 Heuristics based on Universal Dependency (UD) parses (Manning et al., 2014) and automatic co- reference resolution are applied … representing government; special frames for roles 3https://github.com/jflanigan/jamr 4https://stanfordnlp.github.io/CoreNLP 5https://github …
Using Semantic Networks for Question Answering-Case of Low-Resource Languages Such as Swahili
B Wanjawa, L Muchemi – … Conference on Applied Human Factors and …, 2020 – Springer
… There may be need for some additional preprocessing tasks before generating the final candidate SVO eg co-reference resolution, NERs, effect of … Manning, CD, Surdeanu, M., Bauer, J., Finkel, J., Bethard, SJ, McClosky, D.: The stanford CoreNLP natural language processing …
Bootstrapping Chatbot Interfaces to Databases
A Mittal, D Saha, P Jain, J Sen, M Jammi… – 8th ACM IKDD CODS …, 2021 – dl.acm.org
… Language processor takes this input and produces English language sentences using domain vocabulary, paraphrasing, and grammar rules like co-reference resolution. Ex- plaining all the rules are beyond the limit of this paper …
An Annotated Corpus based on Wikipedia
M Strobl, A Trabelsi, O Zaiane – webdocs.cs.ualberta.ca
… 3. Co-reference Resolution (CR) (eg (Lee et al., 2018)): Finding mentions of entities in text that refer to named entities, such as he, she, it or the company, the prince. 4. Relation Extraction (RE) (eg (Takanobu et al., 2019)): Finding …
API-Misuse Detection Driven by Fine-Grained API-Constraint Knowledge Graph
X Ren, X Ye, Z Xing, X Xia, X Xu… – 2020 35th IEEE/ACM …, 2020 – ieeexplore.ieee.org
… We use co-reference resolution technique (as implemented by Stanford CoreNLP [21]) to resolve the pronouns in a API-caveat sentence to the APls that the pronouns represent in the paragraph from which the sentence is extracted …
A Comparative Study on Different Techniques of Sentimental Analysis
KS Peeyusha, G Pooja, S Shreyas… – Soft Computing: Theories …, 2020 – Springer
… Many combine Stanford’s NLP equipment, including Stanford CoreNLP Part-of-Speech (POS) tagger, Named Unit Recognition (NEC), Parser … It touches every aspect of NLP, eg, co-reference resolution, negation handling, and word sense disambiguation, which add more …
Cluster-based mention typing for named entity disambiguation
A Çelebi, A Özgür – Natural Language Engineering – cambridge.org
Cluster-based mention typing for named entity disambiguation.
A corpus of controlled opinionated and knowledgeable movie discussions for training neural conversation models
F Galetzka, CU Eneh, D Schlangen – arXiv preprint arXiv:2003.13342, 2020 – arxiv.org
… Automatically validating this was not trivial, as it requires co-reference resolution and sentiment analysis for our specific data … We used the coref- erence resolution annotator from CoreNLP to replace the references with their entity names …
Interactive text graph mining with a prolog-based dialog engine
P Tarau, E Blanco – International Symposium on Practical Aspects of …, 2020 – Springer
… 5 Related Work. Dependency Parsing. The Stanford neural network based dependency parser [7] is now part of the Stanford CoreNLP toolkit 13 , which also comes with part of speech tagging, named entities recognition and co-reference resolution [13] …
Probing the Natural Language Inference Task with Automated Reasoning Tools
Z Marji, A Nighojkar, J Licato – arXiv preprint arXiv:2005.02573, 2020 – arxiv.org
… R2: Co-reference resolution. ACE does not allow pro- nouns. We use Stanford’s CoreNLP server to identify coref- erence chains within each sentence. If the chain contains a proper noun, that noun is considered the chain’s name; oth- erwise, a default and unique name is used …
KnowText: Auto-generated Knowledge Graphs for custom domain applications
T Matthews, JK Sasikumar, B Boži? – 2020 – openreview.net
… Using NLP platforms (Spacy [9] or NLTK) to perform POS tagging; – Perform co-reference resolution using Spacy’s … Perform dependency parsing to annotate words in the text with their syn- tactic role using python platforms (here we used Stanford coreNLP’s, Stan- fordOpenIE …
Impact of passive and negative sentences in automatic generation of static UML diagram using NLP
R Sanyal – Journal of Intelligent & Fuzzy Systems, 2020 – content.iospress.com
… 1. This methodology employs Stanford universal dependencies from Stanford CoreNLP [13], [5], [30], [17], [7] tool … Fig. 1. Steps followed in the proposed methodology. Generally, co-reference resolution leads to ambigu- ity in the text …
Astraea: Grammar-based Fairness Testing
E Soremekun, S Udeshi, S Chattopadhyay – arXiv preprint arXiv …, 2020 – arxiv.org
… Error Prediction Outcome Pred. Error Bias Sample Discriminatory Test Cases Co reference Resolution (CR) Individual Gender Subjective Pronoun {a/b} = The farmer was passing by. CR(a) == CR(b) CR(a) ={farmer, He} CR(b)={farmer, baker} …
Personizing the prediction of future susceptibility to a specific disease
K Taha, R Davuluri, P Yoo, J Spencer – Plos one, 2021 – journals.plos.org
… OpenNLP provides the following services for processing Natural Language texts. It parses, tokenizes, segments sentences, tags Part-Of-Speech (POS), recog- nizes and extracts named entity, and provides co-reference resolution, etc …
Co-occurrence graph-based context adaptation: a new unsupervised approach to word sense disambiguation
S Rahmani, SM Fakhrahmad… – Digital Scholarship in …, 2020 – academic.oup.com
… erroneous. Also, in co-reference resolution and question answering systems, specifying exact senses of ambiguous terms in a text plays a pivotal role in the accuracy of selecting context features (Agirre and Edmonds, 2007) …
Relation Extraction from Cross-Genre Unstructured Text
P Maitra, D Das – Emerging Technology in Modelling and Graphics, 2020 – Springer
… Using Stanford CoreNLP lemmatizer, extracted verbs are transformed into the corresponding lemma, so that they can be used to search … Further improvement of the present recall factor is possible by introducing a co-reference resolution model or weighted context word scoring …
Financial knowledge graph construction
S Elhammadi – 2020 – open.library.ubc.ca
Learning, knowledge, research, insight: welcome to the world of UBC Library, the second-largest academic research library in Canada.
Reference and Identity in Jewish, Christian, and Muslim Scriptures: The Same God?
DE Buckner – 2020 – books.google.com
Page 1. DENTITY IN JEWISH, 3. AND MUSLMA SCRIPTURES DE BUCKNER ? © O () > <! C/O H |– REFERENCE AND CHRISTIAN Page 2. Reference and Identity in Jewish, Christian, and Muslim Scriptures Page 3. Philosophy …
Semi-Automated Protocol Disambiguation and Code Generation
J Yen, T Lévai, Q Ye, X Ren, R Govindan… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. Semi-Automated Protocol Disambiguation and Code Generation Jane Yen University of Southern California yeny@usc.edu Tamás Lévai Budapest University of Technology and Economics levait@tmit.bme.hu Qinyuan …
Latent Alignment of Procedural Concepts in Multimodal Recipes
HR Faghihi, R Mirzaee, S Paliwal… – arXiv preprint arXiv …, 2021 – arxiv.org
… An example of this is shown in Figure 6, where co-reference resolution is required to answer the question correctly. Figure 6: The images lead the model to understand that ”it” refers to bread rather than sandwich … 2014. The stanford corenlp natural language processing toolkit …
Pattern-based bootstrapping framework for biomedical relation extraction
SS Deepika, TV Geetha – Engineering Applications of Artificial Intelligence, 2021 – Elsevier
… then, the algorithm has been used for numerous Natural Language Processing (NLP) applications across different languages and domain like named entity recognition, parts of speech tagging, noun compound extraction, paraphrasing and co-reference resolution (Sarhan et al …
Towards the Ontologization of the Outsider Art Domain: Position Paper
J Roberto, B Davis – 16th Joint ACL-ISO Workshop on Interoperable …, 2020 – aclweb.org
… such as sentence splitting, tokenisation, part-of-speech (POS) tagger, chunk parsing, name entity recognition and classification (NERC) and co-reference resolution … outsiderartfair.com/ 4 https://rawvision.com/ 5 https://www.nltk.org/ 6 https://stanfordnlp.github.io/CoreNLP/ 7 http …
A Heterogeneous Graph with Factual, Temporal and Logical Knowledge for Question Answering Over Dynamic Contexts
W Zhong, D Tang, N Duan, M Zhou, J Wang… – arXiv preprint arXiv …, 2020 – arxiv.org
… the swamps”. These two locations are the same with the referential relationship but the model fails to identify that. One intuition of solving this type of errors is to employ the co-reference resolution toolkits. 6 Conclusion We present …
Towards Quantifying the Distance between Opinions
S Gurukar, D Ajwani, S Dutta, J Lauri… – Proceedings of the …, 2020 – ojs.aaai.org
… Figure 2: Dependency tree of sample sentence noun phrase. For this, we use co-reference resolution and dependency parsing … To extract the set of words for opin- ion expressions, we carefully defined 14 rules using Stanford CoreNLP’s Semgrex pattern matching system …
Video Object Grounding using Semantic Roles in Language Description
A Sadhu, K Chen, R Nevatia – Proceedings of the IEEE/CVF …, 2020 – openaccess.thecvf.com
… interest. Apart from [8, 76], [27] enforces temporal consistency for video object segmenta- tion and requires the target to be in each frame and [23] use structured representations in videos and language for co-reference resolution …
Sense-Making Machines
V Sarathy – 2020 – search.proquest.com
Page 1. Sense-Making Machines A dissertation submitted by Vasanth Sarathy BS, University of Arkansas; SM, Massachusetts Institute of Technology; JD, Boston University School of Law In partial fulfillment of the requirements for the degree of Doctor of Philosophy in …
Supporting search engines with knowledge and context
N Voskarides – arXiv preprint arXiv:2102.06762, 2021 – arxiv.org
Page 1. arXiv:2102.06762v1 [cs.IR] 12 Feb 2021 Page 2. Page 3. Supporting Search Engines with Knowledge and Context Nikos Voskarides Page 4. Page 5. Supporting Search Engines with Knowledge and Context ACADEMISCH PROEFSCHRIFT …
Extracting supply chain maps from news articles using deep neural networks
P Wichmann, A Brintrup, S Baker… – … Journal of Production …, 2020 – Taylor & Francis
Supply chains are increasingly global, complex and multi-tiered. Consequently, companies often struggle to maintain complete visibility of their supply network. This poses a problem as visibility o…
SRLGRN: Semantic Role Labeling Graph Reasoning Network
C Zheng, P Kordjamshidi – arXiv preprint arXiv:2010.03604, 2020 – arxiv.org
… To solve the multi-hop reasoning problem, some models tried to construct an entity graph using Spacy1 or Stanford CoreNLP (Manning et al., 2014) and then applied a graph model to infer … Coref-GRN (Dhingra et al., 2018) utilize co-reference resolution to build the entity graph …
Extraction of temporal relations from clinical free text: A systematic review of current approaches
G Alfattni, N Peek, G Nenadic – Journal of Biomedical Informatics, 2020 – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …
Automatic text summarization: A comprehensive survey
WS El-Kassas, CR Salama, AA Rafea… – Expert Systems with …, 2020 – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …
Comprehensive Study on Sentiment Analysis: Types, Approaches, Recent Applications, Tools and APIs
B Saju, S Jose, A Antony – 2020 Advanced Computing and …, 2020 – ieeexplore.ieee.org
… library Stanford CoreNLP, which includes features like POS tagger, co reference resolution system, neural network dependency parser and named entity recognizer. Weka: This is an open-source machine learning software primarily used for research and educational purposes …
Analysis and prediction in sparse and high dimensional text data: The case of Dow Jones stock market
OC Sert, SD ?ahin, T Özyer, R Alhajj – Physica A: Statistical Mechanics and …, 2020 – Elsevier
… to accomplish natural language processing tasks, including Apache OpenNLP [2], Stanford CoreNLP [3] and OpeNER [4]. These toolkits provide operations such as tokenizer, sentence splitter, pos tagger, named entity recognition, sentiment analysis, co-reference resolution, etc …
Padchest: A large chest x-ray image dataset with multi-label annotated reports
A Bustos, A Pertusa, JM Salinas… – Medical image …, 2020 – Elsevier
… model (Charniak and Johnson, 2005); finally, the universal dependency graph of each sentence is computed using Stanford CoreNLP (De Marneffe and … This method also deals with co-reference resolution, in which words for locations are related to the entities that they are …
Opinion Mining and Summarization: A Comprehensive Review
AU Jan, MA Khan, N Mukhtar – Journal of Information Communication …, 2020 – jictra.com.pk
… opinionated text [35]. Several NLP toolkits including NLTK [71], OpenNLP and CoreNLP [72] are used to improve the accuracy of feature selection. These toolkits perform different tasks ie POS tagging, word tokenization, name entity recognition and sentence parsing [57]. 3.2 …
Paraphrase identification with Lexical, syntactic and sentential encodings
S Xu, X Shen, F Fukumoto, J Li, Y Suzuki, H Nishizaki – Applied Sciences, 2020 – mdpi.com
Paraphrase identification has been one of the major topics in Natural Language Processing (NLP). However, how to interpret a diversity of contexts such as lexical and semantic information within a sentence as relevant features is still an open problem. This paper addresses the …
Cultural Mapping of Villages Of India
T Sharma – 2020 – web2py.iiit.ac.in
… 28 4.2.2.1 Named Entity Recognition . . . . . 28 vii Page 8. viii CONTENTS 4.2.2.2 Co-Reference resolution . . . . . 30 4.2.2.3 RelationExtraction . . . . . 30 4.2.2.4 MappingtoOntology …
Computational Text Analysis within the Humanities
J Kuhn – Reflektierte Algorithmische Textanalyse, 2020 – degruyter.com
Page 1. Jonas Kuhn Computational Text Analysis within the Humanities How to combine working practices from the contributing fields? Abstract: This position paper is based on a keynote presentation at the COLING 2016WorkshoponLanguageTechnologyforDigitalHumanities …
Relation-Ontology Driven Topic Classification
Q Hao – 2020 – kclpure.kcl.ac.uk
Page 1. This electronic thesis or dissertation has been downloaded from the King’s Research Portal at https://kclpure.kcl.ac.uk/portal/ Take down policy If you believe that this document breaches copyright please contact librarypure …
NLP-assisted software testing: A systematic mapping of the literature
V Garousi, S Bauer, M Felderer – Information and Software Technology, 2020 – Elsevier
… requirement item: If the user enters valid user name and password, then the system should let the user log in. We have used two online tools to do this example analysis: www.corenlp.run and macniece.seas.upenn.edu:4004 …
A Cognitive Method for Automatically Retrieving Complex Information on a Large Scale
Y Wang, B Yao, T Wang, C Xia, X Zhao – Sensors, 2020 – mdpi.com
Modern retrieval systems tend to deteriorate because of their large output of useless and even misleading information, especially for complex search requests on a large scale. Complex information retrieval (IR) tasks requiring multi-hop reasoning need to fuse multiple scattered text …
Topological Data Analysis in Text Processing
S Gholizadeh – 2020 – search.proquest.com
Page 1. TOPOLOGICAL DATA ANALYSIS IN TEXT PROCESSING by Shafie Gholizadeh A dissertation submitted to the faculty of The University of North Carolina at Charlotte in partial fulfillment of the requirements for the degree …
Unsupervised and Supervised Learning of ComplexRelation Instances Extraction in Natural Language
Z Wang – 2020 – repository.tudelft.nl
… to improve performance. This means query expansion will help us locate relations accurately. Thirdly, within document co-reference resolution, it is important to detect name entities as explained by Ji et al. [39]. Although our …
dstlr: Scalable Knowledge Graph Construction from Text Collections
R Clancy – 2020 – uwspace.uwaterloo.ca
… dev.) for Lucene vs. Solr . . . . . 14 3.1 Information Extraction output . . . . . 20 3.2 CoreNLP annotators for information extraction and entity linking . . . . . 24 viii Page 9. List of Figures 1.1 The dstlr architecture . . . . . 2 …
Syntactic and semantic information extraction from NPP procedures utilizing natural language processing integrated with rules
Y Choi, MD Nguyen, TN Kerr Jr – Nuclear Engineering and Technology, 2020 – Elsevier
… outcomes than when applied to general non-technical texts due to the reduction in homonym conflicts and co-reference resolution problems and the … processing tools in accordance with the language used to describe the procedures, such as the Stanford CoreNLP Toolkit [36] or …
Gamifying Language Resource Acquisition
CJ Madge – 2020 – qmro.qmul.ac.uk
Page 1. Gamifying Language Resource Acquisition By CHRISTOPHER JAMES MADGE School of Electronic Engineering And Computer Science QUEEN MARY UNIVERSITY LONDON Submitted in partial fulfillment of the requirements of the Degree of Doctor of Philosophy …
Purposive Visual Imitation for Learning Structured Tasks from Videos
DA Huang – 2020 – search.proquest.com
… 2.2 Related Work Coreference/Reference Resolution in Vision In additional to the core task of coreference or reference resolution in NLP [19, 49, 122 … R is independent of L given A. Here, P (L|A) parses the action nodes from transcriptions using the Stanford CoreNLP pack- age …
Dissecting Fact-Checking Systems: The Impact of Evidence Extraction Methods
PJL Azevedo – 2020 – repositorio-aberto.up.pt
Page 1. FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO Dissecting Fact-Checking Systems: The Impact of Evidence Extraction Methods Pedro José Lourenço Azevedo Mestrado Integrado em Engenharia Informática e Computação …
A Panoramic Survey of Natural Language Processing in the Arab World
K Darwish, N Habash, M Abbas, H Al-Khalifa… – arXiv preprint arXiv …, 2020 – arxiv.org
… development of NLP systems, a number of multi-lingual infrastructure toolkits have been developed, eg, GATE2, Stanford CoreNLP3 and … Performing such a task may employ a large set of NLP tools such as parsing, NER, co-reference resolution, and text semantic representation …
REVISITING RECOGNIZING TEXTUAL ENTAILMENT FOR EVALUATING NATURAL LANGUAGE PROCESSING SYSTEMS
A Poliak – 2020 – jscholarship.library.jhu.edu
Page 1. REVISITING RECOGNIZING TEXTUAL ENTAILMENT FOR EVALUATING NATURAL LANGUAGE PROCESSING SYSTEMS by Adam Poliak A dissertation submitted to The Johns Hopkins University in conformity with the …
A Semantic Question Answering through Heterogeneous Data Source in the Domain of Smart Factory
O Oruç – International Journal on Natural Language Computing …, 2020 – papers.ssrn.com
… 41 Electronic copy available at: https://ssrn.com/abstract=3697829 Page 10. Fig. 3: An example sentence from Stanford CoreNLP [10] … The second finding is that complex paragraphs need a complicated mechanism such as co-reference resolution …
A differentiable relaxation of graph segmentation and alignment for AMR parsing
C Lyu, SB Cohen, I Titov – arXiv preprint arXiv:2010.12676, 2020 – arxiv.org
Page 1. A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing Chunchuan Lyu1 Shay B. Cohen1 Ivan Titov1,2 ILCC, School of Informatics, University of Edinburgh1 ILLC, University of Amsterdam2 …
Enabling End-Users to Create Real-World Robot Applications through Visual Programming Interfaces and Automation
MJY Chung, M Cakmak, RPN Rao, D Fox – 2020 – researchgate.net
Page 1. ©Copyright 2020 Michael Jae-Yoon Chung Page 2. Enabling End-Users to Create Real-World Robot Applications through Visual Programming Interfaces and Automation Michael Jae-Yoon Chung A dissertation submitted …
A Semantic Question Answering in a Restricted Smart Factory Domain Attaching to Various Data Sources
O Oruç – academia.edu
… Fig. 2: An example sentence from Stanford CoreNLP [11]. We specified noun and verb phrases at a basic level so that they are using a shallow parsing that can alleviate the constituency-parsing disambiguations … Fig. 5: Named-Entity Recognition Stanford CoreNLP [11] Fig …
Character-level Representations Still Improve Semantic Parsing in the Age of BERT
R van Noord, A Toral, J Bos – Proceedings of the 2020 Conference on …, 2020 – aclweb.org
… The task is com- plex and comprises other NLP tasks, such as se- mantic role labeling, word sense disambiguation, co-reference resolution and named entity … For the first three sources, we use Stanford CoreNLP (Manning et al., 2014) to parse the documents in our dataset …
A Semantic Question Answering in the Domain of Smart Factories
O Oruc?, U Aßmann – 2020 – easychair.org
Page 1. EasyChair Preprint ? 3005 A Semantic Question Answering in the Domain of Smart Factories Orçun Oruç and Uwe Aßmann EasyChair preprints are intended for rapid dissemination of research results and are integrated with the rest of EasyChair. March 19, 2020 …
Global Trade, National News Frames, and State Public Opinion: Making Sense of US-China Trade, 2008-2018
J Lukito – 2020 – search.proquest.com
Page 1. i Global Trade, National News Frames, and State Public Opinion: Making Sense of US-China Trade, 2008-2018 by Josephine Lukito A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Mass Communication) at the …
Probabilistic inference on uncertain semantic link network and its application in event identification
W Li, H Zhuge – Future Generation Computer Systems, 2020 – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …
Big Data and Social Science: Data Science Methods and Tools for Research and Practice
I Foster, R Ghani, RS Jarmin, F Kreuter, J Lane – 2020 – books.google.com
… Page 11. x Contents 8.5 8.6 Word embeddings and deep learning Text analysis tools . . . . . 8.6.1 The natural language toolkit 8.6.2 Stanford CoreNLP . . . . . 8.6.3 The MALLET . . . . . 8.6.3.1 Spacy.io . . . . . 8.6.3.2 Pytorch Summary . . . . . Resources …
Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERT
R van Noord, A Toral, J Bos – arXiv preprint arXiv:2011.04308, 2020 – arxiv.org
… The task is com- plex and comprises other NLP tasks, such as se- mantic role labeling, word sense disambiguation, co-reference resolution and named entity … For the first three sources, we use Stanford CoreNLP (Manning et al., 2014) to parse the documents in our dataset …
User Review Analysis for Requirement Elicitation
?? – 2020 – core.ac.uk
Page 1. 2020 User Review Analysis for Requirement Elicitation JUAN WANG ?? Thesis submitted in partial fulfilment of the requirements of the award of Doctor of Philosophy in School of Engineering, Computing and Mathematics …
Natural Language Processing and Text Mining with Graph-Structured Representations
B Liu – 2020 – era.library.ualberta.ca
Page 1. Natural Language Processing and Text Mining with Graph-Structured Representations by Bang Liu A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Engineering …
Automatic Characterization of Stories
S Kar – 2020 – uh-ir.tdl.org
Page 1. Automatic Characterization of Stories by Sudipta Kar A dissertation submitted to the Department of Computer Science, College of Natural Sciences and Mathematics in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science …
Natural language processing for social media
AA Farzindar, D Inkpen – Synthesis Lectures on Human …, 2020 – morganclaypool.com
Page 1. 0 n F ARZIND AR • INK P E N N A T UR AL L ANGU A GE P R O CE SSING FOR SO CIAL ME DIA , 3 R D E D . M O R GAN & CL A YPOO L Page 2. Page 3. Natural Language Processing for Social Media Third Edition Page 4. Page 5. Synthesis Lectures on Human …