Published on February 20, 2014
Lexical Simplification Improving understandability, Reducing Errors. Matt Shardlow University of Manchester lexicalsimplification.blogspot.co.uk
The Problem ● Text is everywhere ● But is it understandable? ● Simplification as assistive technology. ● Concentrating on vocabulary 2
Examples ● Technical Medical Language – – ● Hypertension risk factors include obesity,... High blood pressure risk factors include excessive weight,... Legal Language – – ● The Products transacted through the Service are... The Products managed through the Service are... Low Literacy Readers – The plan resolved to increase the frequency of flooding... – The plan determined to raise the amount of flooding... 3
How? ● Practical Simplification of English Text (PSET) – – Replaces low frequency words with high frequency – ● Lexical simplification (Carroll et al. '98) Paraphrasing – Medical language (Deléger and Zweigenbaum '09) – Wikipedia (Yatskar et al. '10) 4
How? ● Word Sense Disambiguation – – ● Language modelling (De Belder and Moens '10) WordNet (Thomas and Anderson '12) Ranking Task – SemEval-2012: Task 1 (Specia et al. '12) – Shared data and evaluation measure. 5
The Pipeline Identification of Complex Words … the frequency of floods Generation of Substitutions Frequency: incidence, amount, recurrence, repetition, prevalence, Word Sense Disambiguation Frequency: incidence, amount, recurrence, repetition, prevalence, Ranking Synonyms by Simplicity 1) amount 2) repetition 3) recurrence 6
Errors in the pipeline ● The event's legacy “hangs in the balance”. ● The event's legacy “falls ● … a vote paving ● … a vote pavement the way for military action. ● … the understanding of neurological disorders. ● … the understanding of neurological disorders. in the balance”. the way for military action. 7
An Experiment ● Baseline simplification system ● Corpus of news texts ● Error categories 8
Error Categories ● Type 1: No error ● Type 2A: An undetected complex word ● Type 2B: A simple word identified as complex ● Type 3A: No substitutions available ● Type 3B: No simpler substitutions available ● Type 4: A change in meaning ● Type 5: The resulting text is more difficult 9
The Pipeline (2) Identification of Complex Words Type 2A / 2B Generation of Substitutions Type 3A / 3B Word Sense Disambiguation Type 4 Ranking Synonyms by Simplicity Type 5 10
Annotation ● Verbose system output ● Single annotator ● One sitting ● Annotations – Recorded – Cross validated 11
Error Distribution - Raw 12
Error Distribution – Independence 13
Where to? ● Working to mitigate the errors ● Evaluation for each pipeline step ● Domain adaptability ● Personal Integration 14
Any Questions References ● J. Carrol, G. Minnen, Y. Canning, S. Devlin, and J. Tait. Practical simplif cation of english newspaper text to assist aphasic readers. AAAI i 1998. ● L. Deléger and P. Zweigenbaum. Extracting lay paraphrases of specialized expressions from monolingual comparable medical corpora. BUCC 2009. ● J. De Belder and M. Moens. Text simplif cation for children. In Proceedings i of the SIGIR workshop on accessible search systems, 2010. ● S. R. Thomas and S. Anderson. WordNet-based lexical simplif cation of a i document. KONVENS 2012. ● L. Specia, S. K. Jauhar, and R. Mihalcea. Semeval-2012 Task 1: English lexical simplif cation. SemEval, 2012. i 15
IAA ● Post-hoc Inter Annotator study ● 3 Annotators ● 20 sentences ● Same format of annotation as first experiment ● Fleiss' kappa calculated ● Moderate kappa agreement of 0.3556 16
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