Adam Wyner


2019

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Making Sense of Conflicting (Defeasible) Rules in the Controlled Natural Language ACE: Design of a System with Support for Existential Quantification Using Skolemization
Martin Diller | Adam Wyner | Hannes Strass
Proceedings of the 13th International Conference on Computational Semantics - Short Papers

We present the design of a system for making sense of conflicting rules expressed in a fragment of the prominent controlled natural language ACE, yet extended with means of expressing defeasible rules in the form of normality assumptions. The approach we describe is ultimately based on answer-set-programming (ASP); simulating existential quantification by using skolemization in a manner resembling a translation for ASP recently formalized in the context of ∃-ASP. We discuss the advantages of this approach to building on the existing ACE interface to rule-systems, ACERules.

2018

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An Annotation Language for Semantic Search of Legal Sources
Adeline Nazarenko | François Levy | Adam Wyner
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2017

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Extracting and Understanding Contrastive Opinion through Topic Relevant Sentences
Ebuka Ibeke | Chenghua Lin | Adam Wyner | Mohamad Hardyman Barawi
Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

Contrastive opinion mining is essential in identifying, extracting and organising opinions from user generated texts. Most existing studies separate input data into respective collections. In addition, the relationships between the topics extracted and the sentences in the corpus which express the topics are opaque, hindering our understanding of the opinions expressed in the corpus. We propose a novel unified latent variable model (contraLDA) which addresses the above matters. Experimental results show the effectiveness of our model in mining contrasted opinions, outperforming our baselines.

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Defeasible AceRules: A Prototype
Martin Diller | Adam Wyner | Hannes Strass
IWCS 2017 - 12th International Conference on Computational Semantics - Long papers

2016

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Legal Text Interpretation: Identifying Hohfeldian Relations from Text
Wim Peters | Adam Wyner
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

The paper investigates the extent of the support semi-automatic analysis can provide for the specific task of assigning Hohfeldian relations of Duty, using the General Architecture for Text Engineering tool for the automated extraction of Duty instances and the bearers of associated roles. The outcome of the analysis supports scholars in identifying Hohfeldian structures in legal text when performing close reading of the texts. A cyclic workflow involving automated annotation and expert feedback will incrementally increase the quality and coverage of the automatic extraction process, and increasingly reduce the amount of manual work required of the scholar.

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Passing a USA National Bar Exam: a First Corpus for Experimentation
Biralatei Fawei | Adam Wyner | Jeff Pan
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Bar exams provide a key watershed by which legal professionals demonstrate their knowledge of the law and its application. Passing the bar entitles one to practice the law in a given jurisdiction. The bar provides an excellent benchmark for the performance of legal information systems since passing the bar would arguably signal that the system has acquired key aspects of legal reason on a par with a human lawyer. The paper provides a corpus and experimental results with material derived from a real bar exam, treating the problem as a form of textual entailment from the question to an answer. The providers of the bar exam material set the Gold Standard, which is the answer key. The experiments carried out using the ‘out of the box’ the Excitement Open Platform for textual entailment. The results and evaluation show that the tool can identify wrong answers (non-entailment) with a high F1 score, but it performs poorly in identifying the correct answer (entailment). The results provide a baseline performance measure against which to evaluate future improvements. The reasons for the poor performance are examined, and proposals are made to augment the tool in the future. The corpus facilitates experimentation by other researchers.

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Scrutable Feature Sets for Stance Classification
Angrosh Mandya | Advaith Siddharthan | Adam Wyner
Proceedings of the Third Workshop on Argument Mining (ArgMining2016)

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Summarising the points made in online political debates
Charlie Egan | Advaith Siddharthan | Adam Wyner
Proceedings of the Third Workshop on Argument Mining (ArgMining2016)

2015

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Argument Discovery and Extraction with the Argument Workbench
Adam Wyner | Wim Peters | David Price
Proceedings of the 2nd Workshop on Argumentation Mining

2014

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Text Analysis of Aberdeen Burgh Records 1530-1531
Adam Wyner | Jackson Armstrong | Andrew Mackillop | Philip Astley
Proceedings of the 8th Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities (LaTeCH)