Papers Definition Extraction

Fine-Tuning BERTs for Definition Extraction from Mathematical Text

In this paper, we fine-tuned three pre-trained BERT models on the task of "definition extraction" from mathematical English written in LaTeX. This is presented as a binary classification problem, where either a sentence …

Mathematical Entities: Corpora and Benchmarks

Mathematics is a highly specialized domain with its own unique set of challenges. Despite this, there has been relatively little research on natural language processing for mathematical texts, and there are few mathemati…

Data Augmentation Method Utilizing Template Sentences for Variable Definition Extraction

The extraction of variable definitions from scientific and technical papers is essential for understanding these documents. However, the characteristics of variable definitions, such as the length and the words that make…

TEGEE: Task dEfinition Guided Expert Ensembling for Generalizable and Few-shot Learning

Large Language Models (LLMs) exhibit the ability to perform in-context learning (ICL), where they acquire new tasks directly from examples provided in demonstrations. This process is thought to operate through an implici…

Parmesan: mathematical concept extraction for education

Mathematics is a highly specialized domain with its own unique set of challenges that has seen limited study in natural language processing. However, mathematics is used in a wide variety of fields and multidisciplinary …

Complex Mathematical Symbol Definition Structures: A Dataset and Model for Coordination Resolution in Definition Extraction

Mathematical symbol definition extraction is important for improving scholarly reading interfaces and scholarly information extraction (IE). However, the task poses several challenges: math symbols are difficult to proce…

Edinburgh at SemEval-2022 Task 1: Jointly Fishing for Word Embeddings and Definitions

This paper presents a winning submission to the SemEval 2022 Task 1 on two sub-tasks: reverse dictionary and definition modelling. We leverage a recently proposed unified model with multi-task training. It utilizes data …

Definition Extraction from Mathematical Texts on Graph Theory in German and English

Defx at SemEval-2020 Task 6: Joint Extraction of Concepts and Relations for Definition Extraction

Definition Extraction systems are a valuable knowledge source for both humans and algorithms. In this paper we describe our submissions to the DeftEval shared task (SemEval-2020 Task 6), which is evaluated on an English …

ACNLP at SemEval-2020 Task 6: A Supervised Approach for Definition Extraction

We describe our contribution to two of the subtasks of SemEval 2020 Task 6, DeftEval: Extracting term-definition pairs in free text. The system for Subtask 1: Sentence Classification is based on a transformer architectur…

Gorynych Transformer at SemEval-2020 Task 6: Multi-task Learning for Definition Extraction

This paper describes our approach to {``}DeftEval: Extracting Definitions from Free Text in Textbooks{''} competition held as a part of Semeval 2020. The task was devoted to finding and labeling definitions in texts. Def…

BERTatDE at SemEval-2020 Task 6: Extracting Term-definition Pairs in Free Text Using Pre-trained Model

Definition extraction is an important task in Nature Language Processing, and it is used to identify the terms and definitions related to terms. The task contains sentence classification task (i.e., classify whether it c…

T\"uKaPo at SemEval-2020 Task 6: Def(n)tly Not BERT: Definition Extraction Using pre-BERT Methods in a post-BERT World

We describe our system (T{\"u}KaPo) submitted for Task 6: DeftEval, at SemEval 2020. We developed a hybrid approach that combined existing CNN and RNN methods and investigated the impact of purely-syntactic and semantic …

UNIXLONG at SemEval-2020 Task 6: A Joint Model for Definition Extraction

Definition Extraction is the task to automatically extract terms and their definitions from text. In recent years, it attracts wide interest from NLP researchers. This paper describes the unixlong team{'}s system for the…

Definition Extraction Feature Analysis: From Canonical to Naturally-Occurring Definitions

Textual definitions constitute a fundamental source of knowledge when seeking the meaning of words, and they are the cornerstone of lexical resources like glossaries, dictionaries, encyclopedia or thesauri. In this paper…

Automated Discovery of Mathematical Definitions in Text with Deep Neural Networks

Automatic definition extraction from texts is an important task that has numerous applications in several natural language processing fields such as summarization, analysis of scientific texts, automatic taxonomy generat…

RGCL at SemEval-2020 Task 6: Neural Approaches to Definition Extraction

This paper presents the RGCL team submission to SemEval 2020 Task 6: DeftEval, subtasks 1 and 2. The system classifies definitions at the sentence and token levels. It utilises state-of-the-art neural network architectur…

DSC IIT-ISM at SemEval-2020 Task 6: Boosting BERT with Dependencies for Definition Extraction

We explore the performance of Bidirectional Encoder Representations from Transformers (BERT) at definition extraction. We further propose a joint model of BERT and Text Level Graph Convolutional Network so as to incorpor…

UPB at SemEval-2020 Task 6: Pretrained Language Models for Definition Extraction

This work presents our contribution in the context of the 6th task of SemEval-2020: Extracting Definitions from Free Text in Textbooks (DeftEval). This competition consists of three subtasks with different levels of gran…

SemEval-2020 Task 6: Definition extraction from free text with the DEFT corpus

Research on definition extraction has been conducted for well over a decade, largely with significant constraints on the type of definitions considered. In this work, we present DeftEval, a SemEval shared task in which p…