AnnIE: An Annotation Platform for Constructing Complete Open Information Extraction Benchmark

09/15/2021
by   Niklas Friedrich, et al.
0

Open Information Extraction (OIE) is the task of extracting facts from sentences in the form of relations and their corresponding arguments in schema-free manner. Intrinsic performance of OIE systems is difficult to measure due to the incompleteness of existing OIE benchmarks: the ground truth extractions do not group all acceptable surface realizations of the same fact that can be extracted from a sentence. To measure performance of OIE systems more realistically, it is necessary to manually annotate complete facts (i.e., clusters of all acceptable surface realizations of the same fact) from input sentences. We propose AnnIE: an interactive annotation platform that facilitates such challenging annotation tasks and supports creation of complete fact-oriented OIE evaluation benchmarks. AnnIE is modular and flexible in order to support different use case scenarios (i.e., benchmarks covering different types of facts). We use AnnIE to build two complete OIE benchmarks: one with verb-mediated facts and another with facts encompassing named entities. Finally, we evaluate several OIE systems on our complete benchmarks created with AnnIE. Our results suggest that existing incomplete benchmarks are overly lenient, and that OIE systems are not as robust as previously reported. We publicly release AnnIE under non-restrictive license.

READ FULL TEXT
research
09/14/2021

BenchIE: Open Information Extraction Evaluation Based on Facts, Not Tokens

Intrinsic evaluations of OIE systems are carried out either manually – w...
research
04/29/2019

Logician: A Unified End-to-End Neural Approach for Open-Domain Information Extraction

In this paper, we consider the problem of open information extraction (O...
research
05/07/2023

Shall We Trust All Relational Tuples by Open Information Extraction? A Study on Speculation Detection

Open Information Extraction (OIE) aims to extract factual relational tup...
research
04/26/2018

Integrating Local Context and Global Cohesiveness for Open Information Extraction

Extracting entities and their relations from text is an important task f...
research
08/28/2018

Graphene: A Context-Preserving Open Information Extraction System

We introduce Graphene, an Open IE system whose goal is to generate accur...
research
05/05/2022

CompactIE: Compact Facts in Open Information Extraction

A major drawback of modern neural OpenIE systems and benchmarks is that ...
research
06/11/2020

A Probabilistic Model with Commonsense Constraints for Pattern-based Temporal Fact Extraction

Textual patterns (e.g., Country's president Person) are specified and/or...

Please sign up or login with your details

Forgot password? Click here to reset