Term Evaluator: A Tool for Terminology Annotation and Evaluation

There are several methods and available tools for terminology extraction, but the quality of the extracted terms is not always high. Hence, an important consideration in terminology extraction is to assess the quality of the extracted terms. In this paper, we propose and make available a tool for annotating the correctness of terms extracted by three term-extraction tools. This tool facilitates term annotation by using a domain-specific dictionary, a set of filters, and an annotation memory, and allows for post-hoc evaluation. We present a study in which two human judges used the developed tool for term annotation. Their annotations were then analyzed to determine the efficiency of term extraction tools by measures of precision, recall, and F-score, and to calculate the inter-annotator agreement rate

Local-Global Vectors to Improve Unigram Terminology Extraction

The present paper explores a novel method that integrates efficient distributed representations with terminology extraction. We show that the information from a small number of observed instances can be combined with local and global word embeddings to remarkably improve the term extraction results on unigram terms. To do so, we pass the terms extracted by other tools to a filter made of the local-global embeddings and a classifier which in turn decides whether or not a term candidate is a term. The filter can also be used as a hub to merge different term extraction tools into a single higher-performing system. We compare filters that use the skipgram architecture and filters that employ the CBOW architecture for the task at hand

Reading Comprehension and Second Language Development in a Comprehension-Based ESL Program

How do experienced ESL instructors plan and organize their teaching practices to make curriculum innovations? The present research sought answers to this question in three different educational contexts, attempting to document the curriculum concepts, pedagogical knowledge, and processes of instructional planning that eight teachers used to create novel courses for adult ESL learners. Findings describe (1) four modes of planning and twelve cycles of information-gathering in the ESL curriculum planning of one teacher, (2) verification of this framework among four additional teachers, as well as (3) an additional framework for documenting teachers' orientations to curriculum content in second language writing instruction, accounting for three teachers' processes of accommodating an instructional innovation into their usual teaching practices

Distributed specificity for automatic terminology extraction

The present article explores two novel methods that integrate distributed representations with terminology extraction. Both methods assess the specificity of a word (unigram) to the target corpus by leveraging its distributed representation in the target domain as well as in the general domain. The first approach adopts this distributed specificity as a filter, and the second directly applies it to the corpus. The filter can be mounted on any other Automatic Terminology Extraction (ATE) method, allows merging any number of other ATE methods, and achieves remarkable results with minimal training. The direct approach does not perform as high as the filtering approach, but it reemphasizes that using distributed specificity as the words' representation, very little data is required to train an ATE classifier. This encourages more minimally supervised ATE algorithms in the future