一句话：提出 TAPHSIR 工具，结合机器学习与 BERT 变体自动检测需求中指代歧义并消解代词。
需求规格说明中代词使用不当可能引发理解歧义。TAPHSIR 面向需求中的指代歧义检测与消解，帮助需求工程师审查代词并修订可能导致误解的用法。该工具采用混合方案：基于机器学习进行歧义检测，并基于 BERT 语言模型变体进行指代消解。给定需求规格说明，TAPHSIR 对每个代词出现判断其是否有歧义，并自动给出代词解释；输出可被需求工程师方便地复核与验证。工具已在 Zenodo 公开。
We introduce TAPHSIR – a tool for anaphoric ambiguity detection and anaphora resolution in requirements. TAPHSIR facilities reviewing the use of pronouns in a requirements specification and revising those pronouns that can lead to misunderstandings during the development process. To this end, TAPHSIR detects the requirements which have potential anaphoric ambiguity and further attempts interpreting anaphora occurrences automatically. TAPHSIR employs a hybrid solution composed of an ambiguity detection solution based on machine learning and an anaphora resolution solution based on a variant of the BERT language model. Given a requirements specification, TAPHSIR decides for each pronoun occurrence in the specification whether the pronoun is ambiguous or unambiguous, and further provides an automatic interpretation for the pronoun. The output generated by TAPHSIR can be easily reviewed and validated by requirements engineers. TAPHSIR is publicly available on Zenodo (https://doi.org/10.5281/zenodo.5902117).
@inproceedings{paperbot7025,
title = {TAPHSIR: towards AnaPHoric ambiguity detection and ReSolution in requirements},
author = {Saad Ezzini and Sallam Abualhaija and Chetan Arora and Mehrdad Sabetzadeh},
booktitle = {FSE},
year = {2022},
doi = {10.1145/3540250.3558928}
}