Diana Maynard


2019

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Team Bertha von Suttner at SemEval-2019 Task 4: Hyperpartisan News Detection using ELMo Sentence Representation Convolutional Network
Ye Jiang | Johann Petrak | Xingyi Song | Kalina Bontcheva | Diana Maynard
Proceedings of the 13th International Workshop on Semantic Evaluation

This paper describes the participation of team “bertha-von-suttner” in the SemEval2019 task 4 Hyperpartisan News Detection task. Our system uses sentence representations from averaged word embeddings generated from the pre-trained ELMo model with Convolutional Neural Networks and Batch Normalization for predicting hyperpartisan news. The final predictions were generated from the averaged predictions of an ensemble of models. With this architecture, our system ranked in first place, based on accuracy, the official scoring metric.

2017

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Comparing Attitudes to Climate Change in the Media using sentiment analysis based on Latent Dirichlet Allocation
Ye Jiang | Xingyi Song | Jackie Harrison | Shaun Quegan | Diana Maynard
Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism

News media typically present biased accounts of news stories, and different publications present different angles on the same event. In this research, we investigate how different publications differ in their approach to stories about climate change, by examining the sentiment and topics presented. To understand these attitudes, we find sentiment targets by combining Latent Dirichlet Allocation (LDA) with SentiWordNet, a general sentiment lexicon. Using LDA, we generate topics containing keywords which represent the sentiment targets, and then annotate the data using SentiWordNet before regrouping the articles based on topic similarity. Preliminary analysis identifies clearly different attitudes on the same issue presented in different news sources. Ongoing work is investigating how systematic these attitudes are between different publications, and how these may change over time.

2016

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Challenges of Evaluating Sentiment Analysis Tools on Social Media
Diana Maynard | Kalina Bontcheva
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This paper discusses the challenges in carrying out fair comparative evaluations of sentiment analysis systems. Firstly, these are due to differences in corpus annotation guidelines and sentiment class distribution. Secondly, different systems often make different assumptions about how to interpret certain statements, e.g. tweets with URLs. In order to study the impact of these on evaluation results, this paper focuses on tweet sentiment analysis in particular. One existing and two newly created corpora are used, and the performance of four different sentiment analysis systems is reported; we make our annotated datasets and sentiment analysis applications publicly available. We see considerable variations in results across the different corpora, which calls into question the validity of many existing annotated datasets and evaluations, and we make some observations about both the systems and the datasets as a result.

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GATE-Time: Extraction of Temporal Expressions and Events
Leon Derczynski | Jannik Strötgen | Diana Maynard | Mark A. Greenwood | Manuel Jung
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

GATE is a widely used open-source solution for text processing with a large user community. It contains components for several natural language processing tasks. However, temporal information extraction functionality within GATE has been rather limited so far, despite being a prerequisite for many application scenarios in the areas of natural language processing and information retrieval. This paper presents an integrated approach to temporal information processing. We take state-of-the-art tools in temporal expression and event recognition and bring them together to form an openly-available resource within the GATE infrastructure. GATE-Time provides annotation in the form of TimeML events and temporal expressions complying with this mature ISO standard for temporal semantic annotation of documents. Major advantages of GATE-Time are (i) that it relies on HeidelTime for temporal tagging, so that temporal expressions can be extracted and normalized in multiple languages and across different domains, (ii) it includes a modern, fast event recognition and classification tool, and (iii) that it can be combined with different linguistic pre-processing annotations, and is thus not bound to license restricted preprocessing components.

2015

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Extracting Relations between Non-Standard Entities using Distant Supervision and Imitation Learning
Isabelle Augenstein | Andreas Vlachos | Diana Maynard
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

2014

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Proceedings of the Third Workshop on Semantic Web and Information Extraction
Diana Maynard | Marieke van Erp | Brian Davis
Proceedings of the Third Workshop on Semantic Web and Information Extraction

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Who cares about Sarcastic Tweets? Investigating the Impact of Sarcasm on Sentiment Analysis.
Diana Maynard | Mark Greenwood
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

Sarcasm is a common phenomenon in social media, and is inherently difficult to analyse, not just automatically but often for humans too. It has an important effect on sentiment, but is usually ignored in social media analysis, because it is considered too tricky to handle. While there exist a few systems which can detect sarcasm, almost no work has been carried out on studying the effect that sarcasm has on sentiment in tweets, and on incorporating this into automatic tools for sentiment analysis. We perform an analysis of the effect of sarcasm scope on the polarity of tweets, and have compiled a number of rules which enable us to improve the accuracy of sentiment analysis when sarcasm is known to be present. We consider in particular the effect of sentiment and sarcasm contained in hashtags, and have developed a hashtag tokeniser for GATE, so that sentiment and sarcasm found within hashtags can be detected more easily. According to our experiments, the hashtag tokenisation achieves 98% Precision, while the sarcasm detection achieved 91% Precision and polarity detection 80%.

2013

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Proceedings of the Joint Workshop on NLP&LOD and SWAIE: Semantic Web, Linked Open Data and Information Extraction
Diana Maynard | Marieke van Erp | Brian Davis | Petya Osenova | Kiril Simov | Georgi Georgiev | Preslav Nakov
Proceedings of the Joint Workshop on NLP&LOD and SWAIE: Semantic Web, Linked Open Data and Information Extraction

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TwitIE: An Open-Source Information Extraction Pipeline for Microblog Text
Kalina Bontcheva | Leon Derczynski | Adam Funk | Mark Greenwood | Diana Maynard | Niraj Aswani
Proceedings of the International Conference Recent Advances in Natural Language Processing RANLP 2013

2012

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Large Scale Semantic Annotation, Indexing and Search at The National Archives
Diana Maynard | Mark A. Greenwood
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This paper describes a tool developed to improve access to the enormous volume of data housed at the UK's National Archives, both for the general public and for specialist researchers. The system we have developed, TNA-Search, enables a multi-paradigm search over the entire electronic archive (42TB of data in various formats). The search functionality allows queries that arbitrarily mix any combination of full-text, structural, linguistic and semantic queries. The archive is annotated and indexed with respect to a massive semantic knowledge base containing data from the LOD cloud, data.gov.uk, related TNA projects, and a large geographical database. The semantic annotation component achieves approximately 83% F-measure, which is very reasonable considering the wide range of entities and document types and the open domain. The technologies are being adopted by real users at The National Archives and will form the core of their suite of search tools, with additional in-house interfaces.

2008

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Benchmarking Textual Annotation Tools for the Semantic Web
Diana Maynard
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

This paper investigates the state of the art in automatic textual annotation tools, and examines the extent to which they are ready for use in the real world. We define some benchmarking criteria for measuring the usability of annotation tools, and examine those factors which are particularly important for a real user to be able to determine which is the most suitable tool for their use. We discuss factors such as usability, accessibility, interoperability and scalability, and evaluate a set of annotation tools according to these factors. Finally, we draw some conclusions about the current state of research in annotation and make some suggestions for the future.

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Evaluating Evaluation Metrics for Ontology-Based Applications: Infinite Reflection
Diana Maynard | Wim Peters | Yaoyong Li
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

In this paper, we discuss methods of measuring the performance of ontology-based information extraction systems. We focus particularly on the Balanced Distance Metric (BDM), a new metric we have proposed which aims to take into account the more flexible nature of ontologically-based applications. We first examine why traditional Precision and Recall metrics, as used for flat information extraction tasks, are inadequate when dealing with ontologies. We then describe the Balanced Distance Metric (BDM) which takes ontological similarity into account. Finally, we discuss a range of experiments designed to test the accuracy and usefulness of the BDM when compared with traditional metrics and with a standard distance-based metric.

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Book Reviews: Information Extraction: Algorithms and Prospects in a Retrieval Context by Marie-Francine Moens
Diana Maynard
Computational Linguistics, Volume 34, Number 2, June 2008 - Special Issue on Semantic Role Labeling

2006

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Creating Tools for Morphological Analysis of Sumerian
Valentin Tablan | Wim Peters | Diana Maynard | Hamish Cunningham
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

Sumerian is a long-extinct language documented throughout the ancient MiddleEast, arguably the first language for which we have written evidence, and is a language isolate (i.e. no related languages have so far been identified). The Electronic Text Corpus of Sumerian Literature (ETCSL), based at theUniversity of Oxford, aims to make accessible on the web over 350 literary workscomposed during the late third and early second millennia BCE. The transliterations and translations can be searched, browsed and read online using the tools of the website. In this paper we describe the creation of linguistic analysis and corpus search tools for Sumerian, as part of the development of the ETCSL. This is designed to enable Sumerian scholars, students and interested laymen to analyse the texts online and electronically, and to further knowledge about the language.

2004

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Automatic Language-Independent Induction of Gazetteer Lists
Diana Maynard | Kalina Bontcheva | Hamish Cunningham
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

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Creation of Reusable Components and Language Resources for Named Entity Recognition in Russian
Borislav Popov | Angel Kirilov | Diana Maynard | Dimitar Manov
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

2003

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Experiments with geographic knowledge for information extraction
Dimitar Manov | Atanas Kiryakov | Borislav Popov | Kalina Bontcheva | Diana Maynard | Hamish Cunningham
Proceedings of the HLT-NAACL 2003 Workshop on Analysis of Geographic References

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OLLIE: On-Line Learning for Information Extraction
Valentin Tablan | Kalina Bontcheva | Diana Maynard | Hamish Cunningham
Proceedings of the HLT-NAACL 2003 Workshop on Software Engineering and Architecture of Language Technology Systems (SEALTS)

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NE Recognition Without Training Data on a Language You Don’t Speak
Diana Maynard | Valentin Tablan | Hamish Cunningham
Proceedings of the ACL 2003 Workshop on Multilingual and Mixed-language Named Entity Recognition

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Multilingual adaptations of a reusable information extraction tool
Diana Maynard | Hamish Cunningham | Kalina Bontcheva
Demonstrations

2002

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Extracting Information for Automatic Indexing of Multimedia Material
Horacio Saggion | Hamish Cunningham | Diana Maynard | Kalina Bontcheva | Oana Hamza | Christian Ursu | Yorick Wilks
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

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A Unicode-based Environment for Creation and Use of Language Resources
Valentin Tablan | Cristian Ursu | Kalina Bontcheva | Hamish Cunningham | Diana Maynard | Oana Hamza | Tony McEnery | Paul Baker | Mark Leisher
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

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How feasible is the reuse of grammars for Named Entity Recognition?
Katerina Pastra | Diana Maynard | Oana Hamza | Hamish Cunningham | Yorick Wilks
Proceedings of the Third International Conference on Language Resources and Evaluation (LREC’02)

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Using GATE as an Environment for Teaching NLP
Kalina Bontcheva | Hamish Cunningham | Valentin Tablan | Diana Maynard | Oana Hamza
Proceedings of the ACL-02 Workshop on Effective Tools and Methodologies for Teaching Natural Language Processing and Computational Linguistics

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Using a text engineering framework to build an extendable and portable IE-based summarisation system
Diana Maynard | Kalina Bontcheva | Horacio Saggion | Hamish Cunningham | Oana Hamza
Proceedings of the ACL-02 Workshop on Automatic Summarization

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GATE: an Architecture for Development of Robust HLT applications
Hamish Cunningham | Diana Maynard | Kalina Bontcheva | Valentin Tablan
Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics

2000

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Creating and Using Domain-specific Ontologies for Terminological Applications
Diana Maynard | Sophia Ananiadou
Proceedings of the Second International Conference on Language Resources and Evaluation (LREC’00)

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Identifying Terms by their Family and Friends
Diana Maynard | Sophia Ananiadou
COLING 2000 Volume 1: The 18th International Conference on Computational Linguistics

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Experience using GATE for NLP R&D
Hamish Cunningham | Diana Maynard | Kalina Bontcheva | Valentin Tablan | Yorick Wilks
Proceedings of the COLING-2000 Workshop on Using Toolsets and Architectures To Build NLP Systems