EXTRA is an open source rules based classification engine, developed by IPTC supported by a grant from Google DNI. Why are rules better than machine learning for breaking news? How can automation better support the manual crafting of news rules.

1. “Extra” by Jeremy Brooks https://flic.kr/p/4aKH3c

2. EXTRA and EXTRA+
Stuart Myles * Associated Press * 6th November 2017
© 2017 IPTC (www.iptc.org) All rights reserved
https://flic.kr/p/kAXGfC

3. Rules-Based Classification
• Rules better for breaking news than statistical methods
– You don’t need 50 examples before you can start tagging
– A rule for a new topic doesn’t require other rules to change
• More consistent and scalable than hand tagging
• Easier to explain why rules classify content
– Machine learning methods are still “black boxes”
– Easier to precisely explain - and correct - mistakes
• You can use your own taxonomy, rules and formats
- Example rules help us drive development of the EXTRA system
- You can use the example rules to see how to develop your own
- Rules could apply IPTC Media Topics or any other taxonomy
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4. EXTRA
EXTraction Rules Apparatus
Rules-based classification of text
Open source software
EXTRA was being developed by the IPTC
€50,000 Grant from the Digital News Initiative
https://www.digitalnewsinitiative.com/fund/
https://iptc.github.io/extra/
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5. Development Process
The EXTRA software is being developed by Infalia
- All software is open source
Two linguists creating rules in English and German
- Samples rules to apply IPTC Media Topics
Example news corpora licensed for EXTRA
- English from Thomson Reuters
- German from APA
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6. EXTRA Components
Elasticsearch
Percolator
+ Custom
Code
Classification
Rule
authoring
Corpus
Testing
Schema
Management
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7. Classification using Percolator
• Elasticsearch
– A sophisticated, open source full-text search engine
– Lets you query documents stored in an index
• Elasticsearch Percolator
– Store queries in an index and match documents to queries
– Classification uses the percolator to match documents to rules
• EXTRA Rule Language
– Rule-writer-friendly language (easier than ES DSL)
– Access to all ES features, plus custom operators
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8. Schema and Rules
• EXTRA Schema
– Documents must be in (or converted to) a JSON format
– But it can be any JSON format you choose
– Allows validating that your rules reference valid fields
• Granular, field-by-field control of analyzers
– Such as whether and how to stem, e.g. by language
– Different ways to tokenize fields, e.g. for slug
– Allow a field to be queried as a whole or tokenized by sentence
or paragraph
– Allows validating that operators are valid by field type
• E.g. to flag that your rule references paragraphs in a field that has
none
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9. Schema and Rules Example
• Two fields - headline and body- with body allowed to be
queried by paragraph
headline
body
body_paragraph
• A rule to require that “angela merkel” and “us elections”
appear in the same paragraph
(prox/unit=paragraph/distance=1
(body adj "angela merkel")
(body adj "us elections")
)
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10. EXTRA Source Code
• The core classification engine
– cql parsers, cql to es mapper, rule schema dict classes,
dao classes, etc
https://github.com/iptc/extra-core
• EXTRA “extra” code
– API, UI, docker files for deployment
https://github.com/iptc/extra-ext
• Open source
– MIT license for EXTRA-specific code
– Apache license for Elasticsearch
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11. EXTRA Timetable
• EXTRA was completed in Summer 2017
• You can access the source code now
– Feedback welcome
• We have applied for a second round of funding: EXTRA+
• Join the (low frequency) email list to stay up-to-date
https://groups.yahoo.com/neo/groups/iptc-extra/info
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12. EXTRA+
Enriching Rule-based Classification of News
with Powerful Semantics
• “aboutness” evaluation
– Given that a story is about a topic, how much is it about it?
• Rule suggestion
– Suggest rules based on a pre-tagged corpus
• Enriched rule operators
– For example, nested “count” operators
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13. Date and Place of Next Meeting
Athens 23rd – 25th April 2018
https://flic.kr/p/atFSAr
ευχαριστώ και αντίο!!
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