Allan Ramsay


2018

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CENTEMENT at SemEval-2018 Task 1: Classification of Tweets using Multiple Thresholds with Self-correction and Weighted Conditional Probabilities
Tariq Ahmad | Allan Ramsay | Hanady Ahmed
Proceedings of The 12th International Workshop on Semantic Evaluation

In this paper we present our contribution to SemEval-2018, a classifier for classifying multi-label emotions of Arabic and English tweets. We attempted “Affect in Tweets”, specifically Task E-c: Detecting Emotions (multi-label classification). Our method is based on preprocessing the tweets and creating word vectors combined with a self correction step to remove noise. We also make use of emotion specific thresholds. The final submission was selected upon the best performance achieved, selected when using a range of thresholds. Our system was evaluated on the Arabic and English datasets provided for the task by the competition organisers, where it ranked 2nd for the Arabic dataset (out of 14 entries) and 12th for the English dataset (out of 35 entries).

2017

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Arabic Tweets Treebanking and Parsing: A Bootstrapping Approach
Fahad Albogamy | Allan Ramsay | Hanady Ahmed
Proceedings of the Third Arabic Natural Language Processing Workshop

In this paper, we propose using a “bootstrapping” method for constructing a dependency treebank of Arabic tweets. This method uses a rule-based parser to create a small treebank of one thousand Arabic tweets and a data-driven parser to create a larger treebank by using the small treebank as a seed training set. We are able to create a dependency treebank from unlabelled tweets without any manual intervention. Experiments results show that this method can improve the speed of training the parser and the accuracy of the resulting parsers.

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Universal Dependencies for Arabic Tweets
Fahad Albogamy | Allan Ramsay
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017

To facilitate cross-lingual studies, there is an increasing interest in identifying linguistic universals. Recently, a new universal scheme was designed as a part of universal dependency project. In this paper, we map the Arabic tweets dependency treebank (ATDT) to the Universal Dependency (UD) scheme to compare it to other language resources and for the purpose of cross-lingual studies.

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Using English Dictionaries to generate Commonsense Knowledge in Natural Language
Ali Almiman | Allan Ramsay
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017

This paper presents an approach to generating common sense knowledge written in raw English sentences. Instead of using public contributors to feed this source, this system chose to employ expert linguistics decisions by using definitions from English dictionaries. Because the definitions in English dictionaries are not prepared to be transformed into inference rules, some preprocessing steps were taken to turn each relation of word:definition in dictionaries into an inference rule in the form left-hand side ⇒ right-hand side. In this paper, we applied this mechanism using two dictionaries: The MacMillan Dictionary and WordNet definitions. A random set of 200 inference rules were extracted equally from the two dictionaries, and then we used human judgment as to whether these rules are ‘True’ or not. For the MacMillan Dictionary the precision reaches 0.74 with 0.508 recall, and the WordNet definitions resulted in 0.73 precision with 0.09 recall.

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A Hybrid System to apply Natural Language Inference over Dependency Trees
Ali Almiman | Allan Ramsay
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017

This paper presents the development of a natural language inference engine that benefits from two current standard approaches; i.e., shallow and deep approaches. This system combines two non-deterministic algorithms: the approximate matching from the shallow approach and a theorem prover from the deep approach for handling multi-step inference tasks. The theorem prover is customized to accept dependency trees and apply inference rules to these trees. The inference rules are automatically generated as syllogistic rules from our test data (FraCaS test suite). The theorem prover exploits a non-deterministic matching algorithm within a standard backward chaining inference engine. We employ continuation programming as a way of seamlessly handling the combination of these two non-deterministic algorithms. Testing the matching algorithm on “Generalized quantifiers” and “adjectives” topics in FraCaS (MacCartney and Manning 2007), we achieved an accuracy of 92.8% of the single-premise cases. For the multi-steps of inference, we checked the validity of our syllogistic rules and then extracted four generic instances that can be applied to more than one problem.

2016

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Fast and Robust POS tagger for Arabic Tweets Using Agreement-based Bootstrapping
Fahad Albogamy | Allan Ramsay
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Part-of-Speech(POS) tagging is a key step in many NLP algorithms. However, tweets are difficult to POS tag because they are short, are not always written maintaining formal grammar and proper spelling, and abbreviations are often used to overcome their restricted lengths. Arabic tweets also show a further range of linguistic phenomena such as usage of different dialects, romanised Arabic and borrowing foreign words. In this paper, we present an evaluation and a detailed error analysis of state-of-the-art POS taggers for Arabic when applied to Arabic tweets. On the basis of this analysis, we combine normalisation and external knowledge to handle the domain noisiness and exploit bootstrapping to construct extra training data in order to improve POS tagging for Arabic tweets. Our results show significant improvements over the performance of a number of well-known taggers for Arabic.

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Unsupervised Stemmer for Arabic Tweets
Fahad Albogamy | Allan Ramsay
Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT)

Stemming is an essential processing step in a wide range of high level text processing applications such as information extraction, machine translation and sentiment analysis. It is used to reduce words to their stems. Many stemming algorithms have been developed for Modern Standard Arabic (MSA). Although Arabic tweets and MSA are closely related and share many characteristics, there are substantial differences between them in lexicon and syntax. In this paper, we introduce a light Arabic stemmer for Arabic tweets. Our results show improvements over the performance of a number of well-known stemmers for Arabic.

2015

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POS Tagging for Arabic Tweets
Fahad Albogamy | Allan Ramsay
Proceedings of the International Conference Recent Advances in Natural Language Processing

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The Application of Constraint Rules to Data-driven Parsing
Sardar Jaf | Allan Ramsay
Proceedings of the International Conference Recent Advances in Natural Language Processing

2014

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Combining strategies for tagging and parsing Arabic
Maytham Alabbas | Allan Ramsay
Proceedings of the EMNLP 2014 Workshop on Arabic Natural Language Processing (ANLP)

2013

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Inference for Natural Language
Amal Alshahrani | Allan Ramsay
Proceedings of the Joint Symposium on Semantic Processing. Textual Inference and Structures in Corpora

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Optimising Tree Edit Distance with Subtrees for Textual Entailment
Maytham Alabbas | Allan Ramsay
Proceedings of the International Conference Recent Advances in Natural Language Processing RANLP 2013

2011

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Exploiting Hidden Morphophonemic Constraints for Finding the Underlying Forms of ‘weak’ Arabic Verbs
Allan Ramsay | Hanady Mansour
Proceedings of the International Conference Recent Advances in Natural Language Processing 2011

2009

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‘Sorry’ is the hardest word
Allan Ramsay | Debora Field
Proceedings of the Workshop on Computational Approaches to Linguistic Creativity

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Using English for commonsense knowledge
Allan Ramsay | Debora Field
Proceedings of the Eight International Conference on Computational Semantics

2008

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Everyday Language is Highly Intensional
Allan Ramsay | Debora Field
Semantics in Text Processing. STEP 2008 Conference Proceedings

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Coling 2008: Companion volume: Demonstrations
Allan Ramsay | Kalina Bontcheva
Coling 2008: Companion volume: Demonstrations

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Translating emphatic/contrastive focus from English to Mandarin Chinese
Chen-li Kuo | Allan Ramsay
Proceedings of the 12th Annual conference of the European Association for Machine Translation

2007

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Deep-reasoning-centred Dialogue
Debora Field | Allan Ramsay
Proceedings of the Eleventh European Workshop on Natural Language Generation (ENLG 07)

2006

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Local Constraints on Sentence Markers and Focus in Somali
Katherine Hargreaves | Allan Ramsay
Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions

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How to change a person’s mind: Understanding the difference between the effects and consequences of speech acts
Debora Field | Allan Ramsay
Proceedings of the Fifth International Workshop on Inference in Computational Semantics (ICoS-5)

2003

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A Constructive View of Discourse Operators
Allan Ramsay | Helen Gaylard
Proceedings of the 2003 EACL Workshop on Dialogue Systems: interaction, adaptation and styes of management

2000

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Unscrambling English word order
Allan Ramsay | Helen Seville
COLING 2000 Volume 2: The 18th International Conference on Computational Linguistics

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Making Sense of Reference to the Unfamiliar
Helen Seville | Allan Ramsay
COLING 2000 Volume 2: The 18th International Conference on Computational Linguistics

1999

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Reference-based Discourse Structure for Reference Resolution
Helen Seville | Allan Ramsay
The Relation of Discourse/Dialogue Structure and Reference

1996

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Aspect and Aktionsart: Fighting or Cooperating?
Allan Ramsay
COLING 1996 Volume 2: The 16th International Conference on Computational Linguistics

1994

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Focus on “Only” and “Not”
Allan Ramsay
COLING 1994 Volume 2: The 15th International Conference on Computational Linguistics

1992

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Genetic NPs and Habitual VPs
Allan Ramsay
COLING 1992 Volume 1: The 14th International Conference on Computational Linguistics

1991

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A Common Framework for Analysis and Generation
Allan Ramsay
Fifth Conference of the European Chapter of the Association for Computational Linguistics

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Intentions in Communication
Allan Ramsay
Computational Linguistics, Volume 17, Number 2, June 1991

1990

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Disjunction without Tears
Allan Ramsay
Computational Linguistics, Volume 16, Number 3, September 1990

1989

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Extended Graph Unification
Allan Ramsay
Fourth Conference of the European Chapter of the Association for Computational Linguistics

1985

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Effective Parsing With Generalised Phrase Structure Grammar
Allan Ramsay
Second Conference of the European Chapter of the Association for Computational Linguistics