AIJul 25, 2022

Graph Querying for Semantic Annotations

arXiv:2207.12166v1584 citationsh-index: 17
Originality Synthesis-oriented
AI Analysis

This tool addresses the need for improved annotation quality and efficiency in natural language processing, but it is incremental as it builds on existing querying and visualization techniques.

The paper tackles the problem of checking consistency and assisting annotation in semantically annotated corpora by presenting GREW-MATCH, an online tool that allows users to query and visualize data, resulting in capabilities for error mining and example retrieval.

This paper presents how the online tool GREW-MATCH can be used to make queries and visualise data from existing semantically annotated corpora. A dedicated syntax is available to construct simple to complex queries and execute them against a corpus. Such queries give transverse views of the annotated data, these views can help for checking the consistency of annotations in one corpus or across several corpora. GREW-MATCH can then be seen as an error mining tool: when inconsistencies are detected, it helps finding the sentences which should be fixed. Finally, GREW-MATCH can also be used as a side tool to assist annotation tasks helping to find annotation examples in existing corpora to be compared to the data to be annotated.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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