Poster used for our VLDB'2015 Demo: (Demo recording available at https://vimeo.com/131232302) Abstract: Information Extraction (IE) is the key technology enabling analytics over unstructured and semi-structured data. Not surprisingly, it is becoming a critical building block for a wide range of emerging applications. To satisfy the rising demands for information extraction in real-world applications, it is crucial to lower the barrier to entry for IE development and enable users with general computer science background to develop higher quality extractors. In this demonstration, we present VINERy, an intuitive yet expressive visual IDE for information extraction. We show how it supports the full cycle of IE development without requiring a single line of code and enables a wide range of users to develop high quality IE extractors with minimal efforts. The extractors visually built in VINERy are automatically translated into semantically equivalent extractors in a state-of-the-art declarative language for IE. We also demonstrate how the auto-generated extractors can then be imported into a conventional Eclipse-based IDE for further enhancement. The results of our user studies indicate that VINERy is a significant step forward in facilitating extractor development for both expert and novice IE developers.

1. System Architecture
(4) User Study
• Experts
• Novice Users
• Much less training needed: Minutes vs. Days
• Unanimously found the system useful
and easy to use
“[Compared to what he has used before] This
is 100 times better.” --- A subject
(2) UI Components
(3) VAQL  AQL
Yunyao Li*, Elmer Kim**, Marc A. Touchette, Ramiya Venkatachalam, Hao Wang
*IBM Research – Almaden, ** Treasure Data, Inc., IBM Silicon Valley Lab
VINERy: A Visual IDE for Information Extraction
(1)VAQL (Visual Annotation Query Language)
• Extract Constructs
• Atomic
• Pre-built
• Dictionary
• Regular Expression
• Literal
• Proximity
• Composite
• Sequence Pattern
• Union
Information extraction is a critical building block for a wide range of emerging applications.
To satisfy the increasing text analytics demands of real-world applications, it is crucial to
lower the barrier to entry and empower novices to develop high
quality IE extractors.
VINERy is SystemT’s latest effort towards this goal.
Automatically generate performant and readable AQL programs
for execution and for further development in AQL, if needed.
Available as part of IBM
BigInsights since 4.0
Watch video demo
• Refinement Constructs
• Projection
• Expression
• Consolidation
• Filter
Document Viewer
CanvasProject Pane
Extractor Catalog Result GridProperty Pane
How does VINERy compare to other existing ways
of performing IE tasks?
much worse much better
1 2 3 4 5
Learning Curve
Time Required
Ease of Use
Effort Required
Try it out Learn more