The Open UniversitySkip to content

Analysing anaphoric ambiguity in natural language requirements

Yang, Hui; De Roeck, Anne; Gervasi, Vincenzo; Willis, Alistair and Nuseibeh, Bashar (2011). Analysing anaphoric ambiguity in natural language requirements. Requirements Engineering, 16(3) pp. 163–189.


This is the latest version of this eprint.

Full text available as:
Full text not publicly available (Version of Record)
Due to publisher licensing restrictions, this file is not available for public download
Click here to request a copy from the OU Author.
DOI (Digital Object Identifier) Link:
Google Scholar: Look up in Google Scholar


Many requirements documents are written in natural language (NL). However, with the flexibility of NL comes the risk of introducing unwanted ambiguities in the requirements and misunderstandings between stakeholders. In this paper, we describe an automated approach to identify potentially nocuous ambiguity, which occurs when text is interpreted differently by different readers. We concentrate on anaphoric ambiguity, which occurs when readers may disagree on how pronouns should be interpreted. We describe a number of heuristics, each of which captures information that may lead a reader to favor a particular interpretation of the text. We use these heuristics to build a classifier, which in turn predicts the degree to which particular interpretations are preferred. We collected multiple human judgements on the interpretation of requirements exhibiting anaphoric ambiguity and showed how the distribution of these judgements can be used to assess whether a particular instance of ambiguity is nocuous. Given a requirements document written in natural language, our approach can identify sentences that contain anaphoric ambiguity, and use the classifier to alert the requirements writer of text that runs the risk of misinterpretation. We report on a series of experiments that we conducted to evaluate the performance of the automated system we developed to support our approach. The results show that the system achieves high recall with a consistent improvement on baseline precision subject to some ambiguity tolerance levels, allowing us to explore and highlight realistic and potentially problematic ambiguities in actual requirements documents.

Item Type: Journal Item
Copyright Holders: 2011 Springer-Verlag London Limited
ISSN: 1432-010X
Extra Information: This paper is an extended version of the paper (Yang et al. 2010) presented at the 18th International Conference on Requirements Engineering (RE’10), which was awarded as the best research paper.
Keywords: nocuous ambiguity; natural language requirements; anaphoric ambiguity; noun-phrase coreference resolution; antecedent preference heuristics; human judgements; machine learning
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 30529
Depositing User: Hui Yang
Date Deposited: 24 Jan 2012 11:16
Last Modified: 07 Dec 2018 17:30
Share this page:

Available Versions of this Item


Altmetrics from Altmetric

Citations from Dimensions

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU